Assessment and biomonitoring indoor environment of buildings

Damp Buildings: Associated Fungi and How to Find Them

The number of buildings experiencing humidity problems and fungal growth appears to be increasing as energy-saving measures and changes in construction practices and climate become more common. Determining the cause of the problem and documenting the type and extent of fungal growth are complex processes involving both building physics and indoor mycology. New detection and identification methods have been introduced, and new fungal species have been added to the list of building-related fungi. However, the lack of standardised procedures and general knowledge hampers the effort to resolve the problems and advocate for an effective renovation plan. This review provides a framework for building inspections on current sampling methods and detection techniques for building-related fungi. The review also contains tables with fungal species that have been identified on commonly used building materials in Europe and North America (e.g., gypsum wallboard, oriented strand board (OSB), concrete and mineral wool). The most reported building-associated fungi across all materials are Penicillium chrysogenum and Aspergillus versicolor. Chaetomium globosum is common on all organic materials, whereas Aspergillus niger is common on all inorganic materials.

Fungal Contamination of Building Materials and the Aerosolization of Particles and Toxins in Indoor Air and Their Associated Risks to Health: A Review

It is now well established that biological pollution is a major cause of the degradation of indoor air quality. It has been shown that microbial communities from the outdoors may significantly impact the communities detected indoors. One can reasonably assume that the fungal contamination of the surfaces of building materials and their release into indoor air may also significantly impact indoor air quality. Fungi are well known as common contaminants of the indoor environment with the ability to grow on many types of building materials and to subsequently release biological particles into the indoor air. The aerosolization of allergenic compounds or mycotoxins borne by fungal particles or vehiculated by dust may have a direct impact on the occupant’s health. However, to date, very few studies have investigated such an impact. The present paper reviewed the available data on indoor fungal contamination in different types of buildings with the aim of highlighting the direct connections between the growth on indoor building materials and the degradation of indoor air quality through the aerosolization of mycotoxins. Some studies showed that average airborne fungal spore concentrations were higher in buildings where mould was a contaminant than in normal buildings and that there was a strong association between fungal contamination and health problems for occupants. In addition, the most frequent fungal species on surfaces are also those most commonly identified in indoor air, regardless the geographical location in Europe or the USA. Some fungal species contaminating the indoors may be dangerous for human health as they produce mycotoxins. These contaminants, when aerosolized with fungal particles, can be inhaled and may endanger human health. However, it appears that more work is needed to characterize the direct impact of surface contamination on the airborne fungal particle concentration. In addition, fungal species growing in buildings and their known mycotoxins are different from those contaminating foods. This is why further in situ studies to identify fungal contaminants at the species level and to quantify their average concentration on both surfaces and in the air are needed to be better predict health risks due to mycotoxin aerosolization.

Surface fungal diversity and several mycotoxin-related genes' expression profiles during the Lunar Palace 365 experiment

BACKGROUND

Chinese Lunar Palace 1 (LP1) is a ground-based bio-regenerative life support system (BLSS) test bed integrating highly efficient plant cultivation, animal protein production, urine nitrogen recycling, and bioconversion of solid waste. To date, there has been no molecular method-based detailed investigation of the fungal community and mycotoxin potential in BLSS habitats. To ensure safe BLSS design for actual space missions, we analyzed the LP1 surface mycobiome and mycotoxin potential during the Lunar Palace 365 project through internal transcribed spacer region 1 (ITS1) amplicon sequencing and quantitative polymerase chain reaction (qPCR) with primers specific for idh, ver1, nor1, tri5, and ITS1.

RESULTS

The LP1 system exhibited significant differences in fungal community diversity compared to other confined habitats, with higher fungal alpha diversity and different community structures. Significant differences existed in the surface fungal communities of the LP1 habitat due to the presence of different occupant groups. However, there was no significant difference between fungal communities in the plant cabin with various occupants. Source tracker analysis shows that most of the surface fungi in LP1 originated from plants. Regardless of differences in occupants or location, there were no significant differences in mycotoxin gene copy number.

CONCLUSIONS

Our study reveals that plants are the most crucial source of the surface fungal microbiome; however, occupant turnover can induce significant perturbations in the surface fungal community in a BLSS. Growing plants reduced fungal fluctuations, maintaining a healthy balance in the surface fungal microbiome and mycotoxin potential. Moreover, our study provides data important to (i) future risk considerations in crewed space missions with long-term residency, (ii) an optimized design and planning of a space mission that incorporates crew shifts and plant growth, and (iii) the expansion of our knowledge of indoor fungal communities with plant growth, which is essential to maintain safe working and living environments. Video Abstract.

Comprehensive health risk assessment of microbial indoor air quality in microenvironments

The higher airborne microbial concentration in indoor areas might be responsible for the adverse indoor air quality, which relates well with poor respiratory and general health effects in the form of Sick building syndromes. The current study aimed to isolate and characterize the seasonal (winter and spring) levels of culturable bio-aerosols from indoor air, implicating human health by using an epidemiological health survey. Microorganisms were identified by standard macro and microbiological methods, followed by biochemical testing and molecular techniques. Sampling results revealed the bacterial and fungal aerosol concentrations ranging between (300–3650 CFU/m³) and (300–4150 CFU/m³) respectively, in different microenvironments during the winter season (December-February). However, in spring (March-May), bacterial and fungal aerosol concentrations were monitored, ranging between (450–5150 CFU/m³) and (350–5070 CFU/m³) respectively. Interestingly, Aspergillus and Cladosporium were the majorly recorded fungi whereas, Staphylococcus, Streptobacillus, and Micrococcus found predominant bacterial genera among all the sites. Taken together, the elevated levels of bioaerosols are the foremost risk factor that can lead to various respiratory and general health issues in additional analysis, the questionnaire survey indicated the headache (28%) and allergy (20%) were significant indoor health concerns. This type of approach will serve as a foundation for assisting residents in taking preventative measures to avoid exposure to dangerous bioaerosols.

Performance Evaluation of Particulate Matter and Indoor Microclimate Monitors in University Classrooms under COVID-19 Restrictions

Optical monitors have proven their versatility into the studies of air quality in the workplace and indoor environments. The current study aimed to perform a screening of the indoor environment regarding the presence of various fractions of particulate matter (PM) and the specific thermal microclimate in a classroom occupied with students in March 2019 (before COVID-19 pandemic) and in March 2021 (during pandemic) at Valahia University Campus, Targoviste, Romania. The objectives were to assess the potential exposure of students and academic personnel to PM and to observe the performances of various sensors and monitors (particle counter, PM monitors, and indoor microclimate sensors). PM1 ranged between 29 and 41 μg m⁻³ and PM10 ranged between 30 and 42 μg m⁻³. It was observed that the particles belonged mostly to fine and submicrometric fractions in acceptable thermal environments according to the PPD and PMV indices. The particle counter recorded preponderantly 0.3, 0.5, and 1.0 micron categories. The average acute dose rate was estimated as 6.58 × 10⁻⁴ mg/kg-day (CV = 14.3%) for the 20–40 years range. Wearing masks may influence the indoor microclimate and PM levels but additional experiments should be performed at a finer scale.

The Improvement of Indoor Air Quality in Residential Buildings in Dubai, UAE

Due to unprecedented urbanization, UAE had built many new residential projects with poor choices of material and ventilation. This social phenomenon is leading UAE to Sick Building Syndrome (SBS) faster than any other countries. The Dubai Municipality regulates the indoor air quality with strict stipulation, but the detailed regulations are still insufficient. The objective of this paper is to measure the indoor air quality of new residential projects in Dubai to suggest the improvement of the regulations for indoor air quality. As a methodology, a field survey was conducted to investigate the status of indoor air pollution in residential buildings. Based on the field survey data, lab experiments for building materials were conducted and a computer simulation on radon gas was conducted. The result had shown that radon gas was mainly detected in new townhouses and labor camp houses, and its concentration was found to exceed the standard. Volatile organic compounds (VOCs) and formaldehyde (CH2O) were mainly detected in showhouses and new townhouses, and the concentration distribution was about 10 times higher than that of outdoors. It was proven that emission concentration of radon gas from various building materials were detected, and the order was red clay, gypsum board, and concrete. Volatile organic compounds (VOCs) are mainly detected in oil paints and PVC floor and the radiation amount of all pollutants increased with temperature increase. In computer simulation, it was found that a new townhouse needs a grace period from 20 days to 6 months to lower the radon gas concentration by 2 pCi/L. This study will serve as a basic data to establish more detailed regulation for the building materials and improve the IAQ standards in Dubai.

Simulation and Analysis of Indoor Air Quality in Florida Using Time Series Regression (TSR) and Artificial Neural Networks (ANN) Models

Exposures to air pollutants have been associated with various acute respiratory diseases and detrimental human health. Analysis and further interpretation of air pollutant patterns are correspondingly important as monitoring them. In the present study, the 24-h and four-month indoor and outdoor PM2.5, PM10, NO2, relative humidity, and temperature were measured simultaneously for a laboratory in Gainesville city, Florida. The indoor PM2.5, PM10, and NO2 concentrations were predicted using multiple linear regression (MLR), time series regression (TSR), and artificial neural networks (ANN) models. The modeling conducted in this study aims to perform a cross comparison study between these models in a symmetric environment. The value of root-mean-square error was improved by 18.33% in comparison with the MLR model. In addition, the value of the coefficient of determination was improved by 24.68%. The ANN model had the best performance and could predict the target air pollutants at 10-min intervals of the studied building with 90% accuracy levels. The TSR model showed slightly better performance compared to the MLR model. These results can be accordingly referred for studies analyzing indoor air quality in similar building types and climate zones.

Application of Airborne Microorganism Indexes in Offices, Gyms, and Libraries

The determination of microbiological air quality in sporting and working environments requires the quantification of airborne microbial contamination. The number and types of microorganisms, detected in a specific site, offer a useful index for air quality valuation. An assessment of contamination levels was carried out using three evaluation indices for microbiological pollution: the global index of microbiological contamination per cubic meter (GIMC/m3), the index of mesophilic bacterial contamination (IMC), and the amplification index (AI). These indices have the advantage of considering several concomitant factors in the formation of a microbial aerosol. They may also detect the malfunction of an air treatment system due to the increase of microbes in aeraulic ducts, or inside a building compared to the outdoor environment. In addition, they highlight the low efficiency of a ventilation system due to the excessive number of people inside a building or to insufficient air renewal. This study quantified the levels of microorganisms present in the air in different places such as offices, gyms, and libraries. The air contamination was always higher in gyms that in the other places. All examined environments are in Northern Italy.

Technology review: prototyping platforms for monitoring ambient conditions

The monitoring of ambient conditions in indoor spaces is very essential owing to the amount of time spent indoors. Specifically, the monitoring of air quality is significant because contaminated air affects the health, comfort and productivity of occupants. This research work presents a technology review of prototyping platforms for monitoring ambient conditions in indoor spaces. It involves the research on sensors (for CO₂, air quality and ambient conditions), IoT platforms, and novel and commercial prototyping platforms. The ultimate objective of this review is to enable the easy identification, selection and utilisation of the technologies best suited for monitoring ambient conditions in indoor spaces. Following the review, it is recommended to use metal oxide sensors, optical sensors and electrochemical sensors for IAQ monitoring (including NDIR sensors for CO₂ monitoring), Raspberry Pi for data processing, ZigBee and Wi-Fi for data communication, and ThingSpeak IoT platform for data storage, analysis and visualisation.