Outdoor Environmental Conditions Research Articles

COVID-19 face masks attracted Cellulomonas and Acinetobacter bacteria and provided breeding haven for red cotton bug (Dysdercus suturellus) and house cricket (Acheta domesticus).

This study investigated the possibility of COVID-19 medical face masks to affect bacterial and macrofaunal communities in open soil environment. An estimated 1.24 trillion of face masks have been used and discarded as a result of the COVID-19 pandemic, with a significant part of this ending up in the soil environment, where they degrade gradually over time. Because bacteria and macrofauna are sensitive indicators of changes in soil ecosystem, we investigated possible impacts of face masks on population, distribution, and diversity of thesesoil species. Effect on soil bacterial community was studied by both culture-based and advanced molecular (metagenomics) approach, while impact on macrofauna was investigated by examining monoliths around heap of masks for soil insects. In both cases, control soil experiments without face masks were also set up and monitored over a period of 48weeks. The study found that the presence of face masks led to a more diverse bacterial community, although no influence on overall bacterial population was evidenced. More importantly, bacteria belonging to the genera Cellulomonas and Acinetobacter were found prominently around face masks and are believed to be involved in biodegradation of the masks. The bacterial community around the masks was dominated by Proteobacteria (29.7-38.7%), but the diversity of species increased gradually with time. Tiny black ants (Monomorium invidium) were attracted to the face masks to take advantage of water retained by the masks during the period of little rainfall. The heaps of face masks also provided shelter and breeding "haven" for soil insects, notably the red cotton bug (Dysdercus suturellus) and house cricket (Acheta domesticus), thereby impacting positively on the population of insect species in the environment. This study provides insights into the actual impacts of face masks on soil organisms under normal outdoor environmental conditions.

Removal of Antibiotic Resistance Genes, Class 1 Integrase Gene and Escherichia coli Indicator Gene in a Microalgae-Based Wastewater Treatment System.

Microalgae-based wastewater treatment systems (AWWTS) have recently shown promise in the mitigation of antibiotic resistance genes (ARGs) from municipal wastewater (MWW). However, due to the large number of ARGs that exist in MWW, the use of indirect conventional water quality parameters to monitor ARGs reduction in wastewater would make the process less burdensome and economically affordable. In order to establish a robust relationship between the ARGs and water quality parameters, the current study employed different microalgae strains in monoculture (CM2, KL10) and multi-species combinations (CK and WW) for the MWW treatment under outdoor environmental conditions. The studied genes were quantified in the MWW influents and effluents using real-time PCR. All the cultures substantially improved the physicochemical qualities of the MWW. Out of the 14 genes analyzed in this study, tetO, tetW, tetX and ermB were decreased beyond detection within the first 4 days of treatment in all the cultures. Other genes, including blaCTX, sul1, cmlA, aadA, int1 and uidA were also decreased beyond a 2 log reduction value (LRV). The mobile genetic element, int1, correlated positively with most of the ARGs, especially sul1 (r ≤ 0.99, p < 0.01) and aadA (r ≤ 0.97, p < 0.01). Similarly, the Escherichia coli indicator gene, uidA, correlated positively with the studied genes, especially with aadA, blaCTX, blaTEM and cmlA (r ≤ 0.99 for each, p < 0.01). Some of the studied genes also correlated positively with total dissolved solids (TDS) (r ≤ 0.98, p < 0.01), and/or negatively with total suspended solids (TSS) (r ≤ -0.98, p < 0.01) and pH (r ≤ -0.98, p < 0.01). Among the tested cultures, both monocultures, i.e., KL10 and CM2 were found to be more consistent in gene suppression than their multi-species counterparts. The findings revealed water quality parameters such as TDS, TSS and E. coli as reliable proxies for ARGs mitigation in AWWTS and further highlight the superiority of monocultures over multi-species cultures in terms of gene suppression from the MWW stream.

Hybrid solar powered desalination system based on air humidification dehumidification integrated with novel distiller: Exergoeconomic analysis

In the current study, an experimental investigation of a hybrid-solar desalination system consisting of humidification–dehumidification unit and a solar distiller (HDH-SD) with exergoeconomic modelling was conducted. Experimental work was performed under outdoor environmental conditions in September 2021. The present work introduces a new humidifier design with helical flow channels and novel solar distiller with multiple sections. The main motivation for analysis is to determine the optimal system operation and design parameters. Exergy-based loss rate, exergy production factor, exergoeconomic parameters, exergy efficiency, and water cost are the main estimated parameters. The result indicates that the maximum HDH-SD system productivity reached 620 L per month. The exergy loss rate in summer is higher than in autumn and spring by about 33% and higher than in winter by about 60%. The exergoeconomic parameter decreases with an increase in interest rates. However, the increase in interest rates causes an increase in water costs. For a lifetime of 30 years and interest rate of 2%, the lowest water cost is about 1.3 $/m3, but the exergoeconomic parameter is the highest. The present study indicates good agreement between the present experimental and numerical investigations.

Binary Dense SIFT Flow Based Position-Information Added Two-Stream CNN for Pedestrian Action Recognition

Pedestrian behavior recognition in the driving environment is an important technology to prevent pedestrian accidents by predicting the next movement. It is necessary to recognize current pedestrian behavior to predict future pedestrian behavior. However, many studies have recognized human visible characteristics such as face, body parts or clothes, but few have recognized pedestrian behavior. It is challenging to recognize pedestrian behavior in the driving environment due to the changes in the camera field of view due to the illumination conditions in outdoor environments and vehicle movement. In this paper, to predict pedestrian behavior, we introduce a position-information added two-stream convolutional neural network (CNN) with multi task learning that is robust to the limited conditions of the outdoor driving environment. The conventional two-stream CNN is the most widely used model for human-action recognition. However, the conventional two-stream CNN based on optical flow has limitations regarding pedestrian behavior recognition in a moving vehicle because of the assumptions of brightness constancy and piecewise smoothness. To solve this problem for a moving vehicle, the binary descriptor dense scale-invariant feature transform (SIFT) flow, a feature-based matching algorithm, is robust in moving-pedestrian behavior recognition, such as walking and standing, in a moving vehicle. However, recognizing cross attributes, such as crossing or not crossing the street, is challenging using the binary descriptor dense SIFT flow because people who cross the road or not act the same walking action, but their location on the image is different. Therefore, pedestrian position information should be added to the conventional binary descriptor dense SIFT flow two-stream CNN. Thus, learning biased toward action attributes is evenly learned across action and cross attributes. In addition, YOLO detection and the Siamese tracker are used instead of the ground-truth boundary box to prove the robustness in the action- and cross-attribute recognition from a moving vehicle. The JAAD and PIE datasets were used for training, and only the JAAD dataset was used as a testing dataset for comparison with other state-of-the-art research on multitask and single-task learning.

A multilevel window state model based on outdoor environmental conditions that captures behavioural variation at room and apartment levels

Occupants’ use of windows can influence the building energy demand, thermal conditions and indoor air quality. Researchers have made substantial efforts to develop probabilistic models to predict the window open/closed state. However, the hierarchical data structure and the heterogeneity in occupant behaviour have been generally neglected in previous modelling efforts. Multilevel modelling can provide an appropriate framework to handle this type of data structure and variability, but this method has rarely been used in the field. This study investigated room- and apartment-level variations in the effects of outdoor environmental variables on the window open state in low-energy apartment buildings in the UK using a multilevel modelling approach. The results showed that the room-level, rather than apartment-level, variation was statistically significant. Meanwhile, the room type (i.e., living room or bedroom) did not significantly affect the relationship between outdoor environmental variables and the window open state. The strength of this study is that the modelling accounted for the hierarchical structure of the data by simultaneously considering room-and apartment- level behavioural variations. By quantifying the significant diversity of occupant behaviour in the natural ventilation of residences, future research can more accurately estimate the variation in building energy and indoor air quality impacts.

Experimental study and model predictions on helium release in an enclosure with single or multiple vents

This paper presents experiments performed at Canadian Nuclear Laboratories (CNL) to examine the dispersion behaviour of helium in a polycarbonate enclosure that was representative of a residential parking garage. The purpose was to gain a better understanding of the effect of buoyancy- or wind-driven natural ventilation on hydrogen dispersion behaviour. Although hydrogen dispersion studies have been reported extensively in the literature, gaps still exist in predictive methods for hazard analysis. Helium, a simulant for hydrogen, was injected near the centre of the floor with a flow rate ranging from 5 to 75 standard litres per minute through an upward-facing nozzle, resulting in an injection Richardson number ranging between 10−1 and 102. The location of the nozzle varied from the bottom of the enclosure to near the ceiling to examine the impact of the nozzle elevation on the development of a stratified layer in the upper region of the enclosure. When the injection nozzle was placed at a sufficiently low elevation, the vertical helium profile always consisted of a homogenous layer at the top overlaying a stratified layer at the bottom. To simulate outdoor environmental conditions, a fan was placed in front of each vent to examine the effect of opposing or assisting wind on the dispersion. The helium transients in the uniform layer predicted with analytical models were in good agreement with the measured transients for most tests. Model improvements are required for adequately predicting transients with primarily stratified profiles or strong opposing wind.

Sol–gel-derived bayberry-like SiO2@TiO2 multifunctional antireflective coatings for enhancing photovoltaic power generation

Multifunctional coatings with broadband antireflective, durable, photocatalytic, and self-cleaning properties can enhance photovoltaic (PV) power generation by reducing the cleaning frequency and surface light reflection of PV modules. However, such coatings must be cost-effective and maintain their functional integrity under harsh outdoor environmental conditions. In this study, bayberry-like SiO2 @TiO2 nanoparticles were prepared by a sol–gel method, and their synthesis procedure and SiO2/TiO2 sol volume ratio were optimized based on the refractive index, transmittance distribution, and methylene blue degradation rate. Afterwards, three-layer gradient refractive index broadband antireflective coatings (TGBA) of the optimized SiO2 @TiO2 nanoparticles were simulated theoretically and systematically characterized by various experimental techniques. The average transmittance of TGBA-coated glass was 8.93% (380–1800 nm) higher than that of undipped glass, and the photocatalytic performance of TGBA was verified by studying methylene blue photodegradation. The self-cleaning performance of TGBA was assessed by outdoor exposure, multi-cycle ultraviolet (UV) irradiation, and dark storage. The durability of TGBA was evaluated by conducting hardness measurements, abrasion testing, thermal cycling, and damp heat tests. The external quantum efficiency and J–V curves of TGBA-coated PV mini-modules revealed that their short-circuit current densities and power conversion efficiencies were substantially higher than those of undipped modules. The proposed multifunctional coatings can enhance PV power generation in harsh environments.

Comparative life cycle assessment of conventional and novel microalgae production systems and environmental impact mitigation in urban-industrial symbiosis

The versatility of microalgae biomass as candidates for various products and bioremediation needs motivates interests towards design and implementation of novel microalgae bioreactors. Conventional open-reactors are reliant on large quantities of sunlight and space while yields are constrained by outdoor environment conditions. Conversely, closed-reactor systems like bubble columns reduces these constrains on microalgae growth while occupying far less space at the expense of high energy demands, notably from lighting systems. A novel patented closed reactor design has recently been proposed that improves the bubble column concept with an efficient and effective lighting system. The present study uses Life Cycle Assessment approach to compare the environmental performance of conventional reactors and the proposed internally luminated novel closed reactor design, expressing impacts per kg biostimulant for the Scenedesmus almeriensis harvest from such units. All performance data was collected from a pilot facility in Almeria, Spain. Urban-industrial symbiosis scenarios are also portrayed in the study using wastewater and incinerator flue gas. Results show that under synthetic nutrient and carbon inputs in Spanish pilot operations, the cumulative energy demand for the novel photobioreactors is similar to conventional vertically-stacked horizon bioreactors but are substantially more demanding than conventional open reactors. However, when leveraging renewable energy sources and the photosynthesis process to consume wastestreams in urban-industrial symbiosis scenarios, the novel photobioreactor was able to achieve up to 80 % improvements in several impact categories e.g. eutrophication and climate change. Impact mitigation credits per kg dwt biomass across all energy scenarios in symbiosis amount to ≈1.8 kg CO2eq and ≈0.09 kg PO4 eq. This highlights that such closed and internally illuminated photobioreactors can be competitive with conventional reactors, and have potential to harness photosynthesis to reduce environmental burdens in an urban-industrial symbiosis setting. Possible economies of scale and the associated potential gains in efficiencies are further discussed.

Behaviour in public open spaces: A systematic review of studies with quantitative research methods

Public open spaces are important assets that play a significant role in city lives, based on which a great number of behaviour-based studies are being conducted. These studies often use one or more case studies to observe people's preferences and usage habits and to investigate their influencing factors such as outdoor thermal comfort, environmental conditions, urban configuration, and local settings. Because the subject is complex and falls within the purview of multiple academic disciplines, it is a challenging task to understand the current status and development trends of existing studies. To fill this gap, this article presents a systematic review of quantitative evidence-based behaviour studies in public open spaces. Following the PRISMA method and searching using eight academic search engines, full texts of 116 research articles have been included for this review. The main contributions of this review are that: (1) it proposed a relatively complete system that categorizes people's behaviour in public open spaces; (2) it introduced outdoor subjective influencing procedure including behaviour, feeling and health impacts; (3) the review illustrated the distribution of existing research as well as research trends; and finally (4) the article also timely discussed the influence of the COVID-19 on people's behaviour in public open spaces. The authors consider this article to be useful as it can facilitate further behaviour-based studies in public open spaces. With a robust classification and future trend discussion of factors associated, fellow researchers, urban designers, city managers, and policymakers are easier to integrate and use the knowledge learned. • A systematic review of 116 quantitative studies on behaviour in public open spaces. • Lists of behaviour types, subjective feedbacks, and objective influencing factors. • A summary of behaviour studies in public open spaces during the COVID-19.

Process engineering strategy for large scale outdoor cultivation of Tetradesmus obliquus CT02 coupled with pH guided CO2 feeding

A novel CO2 tolerant microalga Tetradesmus obliquus CT02, was previously evaluated to be a suitable bio refinery platform for synthesis of bioactive molecules, biodiesel, and biofertilizer. In the present study, a process engineering strategy was developed targeting improved growth performance of the strain at large scale under fluctuating outdoor environmental conditions. The strategy relies on maintaining pH of the culture at its optimal value via cascade control with CO2 feeding. The strategy was developed at laboratory scale bubble column photobioreactor under diurnal variation of simulated sunlight intensity and was further validated through growth performance of the strain under outdoor conditions in a 100L airlift bioreactor. Under laboratory condition, 53.3% and 85.16% improvement in biomass concentration (1.87gL-1) and productivity (114.8mgL-1 day-1) was achieved as compared to the uncontrolled pH, respectively. The strategy demonstrated a significant improvement in biomass concentration and productivity by 225.7% and 121.6% respectively, compared to the pH uncontrolled batch, even under outdoor fluctuating environmental condition.

Comparison Experiment on Floor Surface Temperature Change and Energy Consumption in PCM Radiant Heating System

Purpose: The insulation performance of exterior walls, roofs, windows, etc. has improved with the strengthening of energy saving laws and has reached the current passive level. However, due to the increasing demand for achieving zero energy and improving indoor comfort, additional research is needed. Therefore, in this study, a comparative experiment was performed for the purpose of examining the phase change temperature of a phase change material (PCM) in order to apply it to an underfloor radiant heating system. Method: A mock-up affected by outdoor environmental conditions was constructed. Two mock-up rooms were equipped with a general radiant heating system and a PCM radiant heating system, respectively. PCMs with phase change temperatures of 44 and 35℃ were used, and when the same room temperature conditions were maintained, the change in floor surface temperature and energy consumption of the rooms installed with the general and PCM systems were measured and compared. Result: As a result of the experiment, when the PCM was applied, the floor surface temperature was higher than that obtained with the general system. In particular, when the 44℃ PCM was applied, the floor surface temperature was the highest. However, in terms of energy consumption and floor temperature maintenance performance, it was found that applying the 35℃ PCM was the most advantageous.

Mixed-Mode Ventilation in HVAC System for Energy and Economic Benefits in Residential Buildings

In the U.S., approximately 47% of the total electricity use comes from residential buildings. Most of the residential buildings use HVAC system to ventilate, cool, or heat the indoor environmental spaces mechanically, rather than using natural outdoor air in transition seasons, even though the outdoor environmental conditions are favorable for indoor thermal comfort. In this case, an HVAC system using mixed-mode ventilation with an appropriate ratio of using indoor air and outdoor air could decrease the energy use in residential buildings. This research uses high-granular HVAC electricity use data with indoor thermostat data and outdoor weather data from residential buildings in Austin, Texas, to evaluate the benefits of energy and economics when using HVAC mixed-mode ventilation in spring and fall transition seasons. The results demonstrate that the household owners could save approximately 150.79 kWh of total HVAC energy use and 24.41% of HVAC cost in spring transition months (April/May), and similarly, 143.86 kWh of energy use and 27.2% cost savings in fall transition months (October/November). The results could support further study to use automatically operated windows for natural ventilation to reduce energy use in residential buildings toward sustainable development.

Investigation on window opening behavior in naturally ventilated hostels of warm and humid climate

A window is an inevitable element of a naturally ventilated building, and its usage improves indoor environmental conditions. Various research has presented window opening behavior models, stating that it may vary with region, climate, season, building type and many more environmental and non-environmental factors. Major studies in India relied on survey data and were not focused on continuous monitoring. Limited occupants’ behavior studies have been reported in warm and humid climatic zones, specifically in hostel buildings. Also, a realistic description of occupants’ window opening behavior is require for more accurate evaluation of building performance using energy simulation. Therefore, there is a need to study the window opening behavior to predict the indoor environment more accurately by using energy simulation tools. In this context, a one-year field research involving questionnaire survey, physical observation, and monitoring was conducted in different hostel buildings in Tiruchirappalli, India. Logistic models were developed to predict the window state in hostel buildings in warm and humid region based on physical observational and long-term monitoring data. It is found that window use is influenced by season, time of the day, weekdays, floor level, buildings’ orientation, user type, and gender. Results also showed that insects and animal menace (snakes, squirrels, lizards, mosquitoes etc.) impede window opening behavior. The study also presented a logistic model for window opening behavior based on outdoor environment conditions for simulation modeling.

건강 실내공기질(IAQ) 유지를 위한 강화학습 기반 환기 시스템, 공기 청정기의 최적 통합 제어

In building industry, indoor environmental conditions can be maintained by using a simple rule based control such as setting a specific temperature or air flow rates for a HVAC system to maintain thermal comfort and IAQ. This simple control scheme can cause inefficient building operation especially multi environmental control devices are exist in the space. Also it does not reflect the changes in occupant behavior and indoor–outdoor environmental conditions. To overcome this limitation, we suggest a new control method using a Double deep Q-network(DDQN) which utilizes a data-driven approach to find the optimal control with various indoor environmental control devices.

Preliminary Results on Natural Aging of GFRP-Reinforced Masonry Components Exposed to Outdoor Environmental Conditions

Fiber reinforced polymers (FRP) have been widely used for strengthening and repair of masonry structures since the 1990s. Although the short-term performance of such systems has been extensively studied, their durability and long-term behavior are still scarcely known. Therefore, a better understanding of the corresponding degradation mechanisms and durability issues is of major interest, especially in cases of externally bonded systems where the materials are prone to undergo a more severe decay. Different accelerated aging tests have been developed in order to simulate weathering conditions in a shorter time: water immersion, freeze-thaw, hygrothermal cycles, salt crystallization, UV radiation, etc. Nonetheless, accelerated aging data cannot be used to make reliable service life estimations without a clear correlation with real environmental processes. In this study, we present the preliminary results (3/12 years) of a real exposure experimental campaign devoted to analyzing the natural aging of masonry components reinforced with externally bonded glass fibers (GFRP). The aging conditions consist of: (a) direct outdoor exposure, i.e. outdoor hygrothermal variation + sun and rain; (b) indirect outdoor exposure, i.e. outdoor hygrothermal variation + sheltered from sun and rain; (c) laboratory conditions as control group. The specimens consist of solid extruded fired-clay bricks strengthened with unidirectional GFRP sheets following the wet lay-up procedure. The aging effects on bond performance are studied by means of single-lap shear tests. Finally, the effect of brick surface treatment and the application of an external render on bond durability is investigated.

Temperature Dependence of Optical Couplant Grease Transmission at UV and Visible Wavelengths

Optical couplant greases based on polydimethylsiloxane (PDMS) may be employed in devices such as scintillator-based radiation detectors that operate in extreme environmental conditions. The optical transmission of Dow Corning DOWSIL Q2-3067 optical couplant grease was measured at room temperature as a function of wavelength (200–800 nm) and grease thickness (0.13–1 mm). Across the spectral range, transmission decreased with increasing thickness, and the increase was more pronounced at wavelengths < 400 nm. An effective ultraviolet (UV) cutoff wavelength of ~270 nm was found, independent of grease thickness, although a weak transmission feature was observed below this cutoff at 233 nm. The optical transmission spectra exhibited a dependence on temperature, increasing with increasing temperature to 50 °C and decreasing with decreasing temperature to −10 °C. This temperature dependence was more pronounced at wavelengths < 400 nm and for thicker grease layers. Below −10 °C, transmission decreased sharply for all wavelengths. This decrease was correlated with a sharp increase in viscosity, indicating that the grease undergoes a thermal transition at −11 °C ± 1 °C. This thermal transition occurs more slowly with decreasing temperature for thinner layers of grease, but all measured grease thicknesses were reasonably opaque at temperatures below −20 °C. These results will aid in predicting the optical and mechanical performance of optical systems such as radiation detectors exposed to extreme outdoor environmental conditions.

Analysis of photovoltaic system under over-irradiation conditions in arid climate

ABSTRACT Photovoltaic systems are sensitive to weather conditions in terms of fluctuation, intermittentness and randomness, which could be affected drastically by the factors such as fast variation from sunlight conditions, environment temperature, cloud shadings under outdoor environmental conditions. The performance of photovoltaic systems could pose greater impact on the security and stability to the power grid especially under extreme irradiance condition. This paper established a mathematical analysis model for photovoltaic system under over-irradiation (OI) condition (>1000 W/m2) combined with the experimental data of a 5.605 kWp monocrystal silicon modules system from 2019 to 2020 in arid climate. The result evaluated the data in aspects of amplitude, frequency, velocity and duration of the performance of the system along with the weather data. The results show that the yield of the system under OI status accounts for 15.09% of the total energy generation, the maximum operating current exceeded the short-circuit current by 26.8% with average duration reaches 272 seconds. Finally, the four typical OI days were chosen from the date and demonstrated that the fuses of the string and inverters in the system would undertake an over-rated status over 12,050 seconds, which raised a challenge to the response time of the inverter and the MPPT algorithm as well as the fuses reliability.

Advanced HRT-Controller Aimed at Optimising Nitrogen Recovery by Microalgae: Application in an Outdoor Flat-Panel Membrane Photobioreactor

A fuzzy knowledge-based controller of hydraulic retention time (HRT) was designed and tested in an outdoor membrane photobioreactor (MPBR) to improve nitrogen recovery from a microalgae cultivation system, maintaining the algae as photosynthetically active as possible and limiting their competition with other microorganisms. The hourly flow of the MPBR system was optimised by adjusting the influent flow rate to the outdoor environmental conditions which microalgae were exposed to at any moment and to the nitrogen uptake capacity of the culture. A semi-empirical photosynthetically active radiation (PAR) prediction model was calibrated using total cloud cover (TCC) forecast. Dissolved oxygen, standardised to 25 °C (DO25), was used as an on-line indicator of microalgae photosynthetic activity. Different indexes, based on suspended solids (SS), DO25, and predicted and real PAR, were used as input variables, while the initial HRT of each operating day (HRT0) and the variation of HRT (ΔHRT) served as output variables. The nitrogen recovery efficiency, measured as nitrogen recovery rate (NRR) per nitrogen loading rate (NLR) in pseudo-steady state conditions, was improved by 45% when the HRT-controller was set in comparison to fixed 1.25-d HRT. Consequently, the average effluent total soluble nitrogen (TSN) concentration in the MPBR was reduced by 47%, accomplishing the discharge requirements of the EU Directive 91/271/EEC.

Evaluation of Selected Algorithms for Air Pollution Source Localisation Using Drones

Polluted air causes enormous damage to human health. There is a high demand to find a solution for locating the places of illegal waste incineration due to the persistent smog problem. The use of multi-rotor drones for that purpose has now become one of the important research topics. The aim of the work was to check the possibility of using simple algorithms to search for the source of pollution. The algorithms that require low computing power, which may be part of the robot’s measurement and the control system’s internal software, were considered. The focus was on building a system based on a single robot that independently searches an area of a certain size. The simulation of the accuracy and scalability of the three different search algorithms was analysed for areas up to 200 m × 200 m. Two multi-rotor robots were prepared for the fieldwork. The validation of the two selected algorithms was carried out in outdoor environmental conditions. The fieldwork tests were carried out in areas with a maximum size of 100 m × 100 m. The obtained results were different, in particular on the wind speed and direction and the intensity of the pollution source. The random influence of these factors can verify the operation of the proposed system in practical applications. The difference between the true and the position of the source indicated by the robot was up to 15 m. That difference depended on the mutual arrangement of the measurement points and the pollution source location.

A progressive comparison of the novel pulse and conventional steady state methods of measuring the airtightness of buildings

Differing from the steady fan pressurisation method (FP) that takes airtightness measurement at high pressures, the Pulse technique takes a dynamic approach and offers low-pressure measurements. Despite different measurement pressures, the interest for direct comparison between the results given by both methods remains strong in research and practice. When testing a typical dwelling, achieving a comparison in an overlapped pressure range comes with difficulties due to Pulse’s low-pressure measurement. In this paper, experimental investigations were performed in two independent studies to enable measurements over an overlapped pressure range under both outdoor and indoor environments. Results in the outdoor environment showed that the FP installation could account for a significant proportion of the air leakage of tested spaces in particular the ones with an airtight enclosure, thereby contributing to the deviation (42-60%) between both testing methods. Such deviation was reduced when sealing is applied around the FP frame. Results in the indoor environment where the impact of outdoor environmental conditions, installation and model difference was reduced showed that a better agreement (0.6-9.6%) was achieved in a range of leakage levels.