ABSTRACT
The outbreak of SARS-CoV-2 (COVID-19) has attracted much attention to study its possible presence and airborne transmission. The possibility of COVID-19 airborne transmission in indoor environments is debatable. The present study examined the concentration of viral RNA-containing particles produced directly or indirectly by breathing or coughing of confirmed COVID-19 patients or by carriers without symptoms. Some studies do not accept this method of transmission (COVID-19 airborne transmission). The present study aimed to measure the possible exposure of health care personnel to SARS-CoV-2 particles that may have been suspended in the air to respond to the hypothesis of COVID-19 airborne transmission. Airborne particle sampling was performed using impingement method based on NIOSH (chapter BA) and ASHRAE. Selection of sampling sections was in line with the WHO guidelines. The samples were analyzed using RT-PCR technique. Based on the given results, airborne particles of COVID-19 may present in the air and affect the health of hospital personnel. In fact, the analysis of gene expression in ambient conditions and thereby aerosol transmission of SARS-CoV-2 through air is possible and may lead to occupational exposure of health care personnel. Furthermore, it was found that airborne emission of COVID-19 through the breathing zone of patients, particularly in ICU wards with confirmed cases of COVID-19, may be higher than in other ICU wards. Also, the demonstrated results showed that there is a possibility of reaerosolization (reintroduction) of previously airborne SARS-CoV-2 particles into the atmosphere due to health care personnel frequently walking between different wards and stations of ICU.
ABSTRACT
Providing evidence of potential changes in the climate has become increasingly important as it is the first step towards adopting mitigation and adaptation measures and planning for urban resilience. In this study a statistical analysis of the ambient air temperature time series over Sydney, Australia during 1970-2016 has been carried out with the aim to investigate potential changes towards higher temperatures. The dataset has been statistically analyzed using different techniques, concluding that the investigation should be performed on a monthly basis. A persistence analysis was conducted using different statistical approaches to investigate the dependence between consecutive monthly and daily ambient air temperature values. A trend analysis of the ambient air temperature and degree days time series has been conducted using linear regression to estimate the linear trend (slope) and its statistical significance (using a Student-t-test) and the Kendall-Mann test to identify the time at which the tendency starts to occur as well as the time after which it becomes statistically significant.
