Parametric modeling study for blown-dust secondary pollution and optimal ventilation velocity during tunnel construction.

Tunnel construction often relies on drilling and blasting. High dust pollution is one of the primary problems of drilling and blasting construction. The level of secondary blown dust pollution caused by ventilation matches that of dust pollution caused by drilling construction. In this study, a critical flow model and blown dust rate model for deposited dust were established via force analysis, which was validated against the test data. The research results showed that the characteristic airflow velocity for blowing dust particles with a 100 µm diameter reached approximately 0.42 m/s for tunnel diameter is 10 m, and the ventilation Re values under smooth and rough conditions were 2.3 × 105 and 1.4 × 105, respectively. Furthermore, when ventilation Re reached 4 × 105, the blown dust pollution rate caused by ventilation under smooth conditions was approximately 1.8 × 10-2 kg/s. If dust particle size is more or less the critical dust particle size, the characteristic airflow velocity was increased. Moreover, the optimal velocity at which the deposited dust does not flow or move during tunnel construction was related to the tunnel size and roughness. For the smooth tunnel with a diameter of 10 m, the optimal ventilation velocity was 3.5 m/s. When the tunnel roughness was increased from 0.005 to 0.5 m, the optimal ventilation velocity decreased from 3.3 to 1.6 m/s. The deposited dust critical flow model and blown dust pollution rate model established in this study provide a sound theoretical basis for selecting the optimal velocity of tunnel ventilation and recognizing the risks of secondary blown dust pollution due to ventilation.

Temporal variation of airborne fungi in university library rooms and its relation to environmental parameters and potential confounders.

Indoor airborne fungi have been associated with adverse human health effects. Therefore, it is important to understand the causes of underlying variation in airborne fungi in indoor environments. This study consequently aimed to investigate the association between indoor fungi with temporal variation, environmental parameters, and potential confounders over 10 months in four library rooms using Andersen samplers. Indoor fungal concentrations peaked in October and were lowest in March in both stack rooms, whereas the highest concentrations in both reading rooms were observed in September with lowest concentrations in July. Nonparametric analyses revealed higher fungal concentrations in the rooms that were significantly associated with relative humidity ≥ 60%, PM2.5 ≥ 35 µg/m3, number of people ≥ 16, open windows, working air conditioners, and room area < 400 m2. Multiple linear regression modeling for the library building considering only continuous variables revealed that relative humidity, PM2.5, and the number of people were significant predictors of fungal concentrations. Additionally, the model with continuous and categorical variables suggested that relative humidity, PM2.5, the number of people, ceiling fan condition, window state, and air conditioner operating status were significant predictor variables of concentrations. Outdoor fungal concentrations were a significant predictor for the two models of indoor fungal concentrations for each room. Ceiling fan or air conditioner operation was associated with altered fungal particle concentrations. These results provide a deeper understanding of indoor air fungal quality.

On-site investigation of the concentration and size distribution characteristics of airborne fungi in a university library.

It is important to investigate fungal air quality in libraries because they represent a complex indoor environment. The aim of the study was to quantitatively investigate airborne fungal contamination levels based on field measurements in autumn and winter in four selected library rooms (compact stack, lending room, reading room, study room) in a university library building, as well as the effects of several factors on the culturability of airborne fungi. Airborne fungal levels varied by room, with the highest fungal levels in the reading room (634 ± 275 CFU/m3) and the lowest in the lending room (486 ± 177 CFU/m3). Airborne fungal concentrations were significantly different with seasonal variation (p < 0.05) for all rooms except for the reading room. The size distribution analysis showed that the most airborne fungi were 1.1-3.2 µm in size; based on the schematic diagram of the human respiratory system, more than 80% of airborne fungi could be deposited in the lower respiratory tract (0.65-4.7 µm). Indoor/outdoor airborne fungal concentration ratios were below 1.0 for all four rooms during autumn and winter, showing that outdoor fungi are the main source of indoor fungi. Pearson correlations showed that the fungal concentration was significantly positively correlated with both temperature (r = 0.531, p < 0.05) and relative humidity (r = 0.555, p < 0.05). Indoor temperature, indoor relative humidity and number of open windows significantly positively affected airborne fungal concentration in a multiple linear regression model (p < 0.05). This paper provides fundamental data on fungal contamination that can help experts in indoor air quality to develop guidelines for airborne fungi in libraries and create a safe environment for library patrons and staff.