Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects.

The Wells-Riley model invokes human physiological and engineering parameters to successfully treat airborne transmission of infectious diseases. Applications of this model would have high potentiality on evaluating policy actions and interventions intended to improve public safety efforts on preventing the spread of COVID-19 in an enclosed space. Here, we constructed the interaction relationships among basic reproduction number (R0) - exposure time - indoor population number by using the Wells-Riley model to provide a robust means to assist in planning containment efforts. We quantified SARS-CoV-2 changes in a case study of two Wuhan (Fangcang and Renmin) hospitals. We conducted similar approach to develop control measures in various hospital functional units by taking all accountable factors. We showed that inhalation rates of individuals proved crucial for influencing the transmissibility of SARS-CoV-2, followed by air supply rate and exposure time. We suggest a minimum air change per hour (ACH) of 7 h-1 would be at least appropriate with current room volume requirements in healthcare buildings when indoor population number is < 10 and exposure time is < 1 h with one infector and low activity levels being considered. However, higher ACH (> 16 h-1) with optimal arranged-exposure time/people and high-efficiency air filters would be suggested if more infectors or higher activity levels are presented. Our models lay out a practical metric for evaluating the efficacy of control measures on COVID-19 infection in built environments. Our case studies further indicate that the Wells-Riley model provides a predictive and mechanistic basis for empirical COVID-19 impact reduction planning and gives a framework to treat highly transmissible but mechanically heterogeneous airborne SARS-CoV-2.

Assessing regional emissions of vehicle-based tire wear particle from macro-to micro/nano-scales with pandemic lockdowns and electromobility scenarios implications.

Despite increasing the public awareness of ubiquity of microplastics (MPs) in air, the issue on particular source of tire wear particles (TWPs) emission into atmosphere and their exposure-associated human health has not received the attention it deserves. Here we linked vehicle kilometers traveled (VKT) estimates covering demography, socio-environmental, and transportation features and emission factors to predict regional emission patterns of TWP-derived atmospheric MPs. A data-driven probabilistic approach was developed to consider variability across the datasets and uncertainty of model parameters in terms of country-level and vehicle-type emissions. We showed that country-specific VKT from billion to trillion vehicle-kilometer resulted in 103-105 metric tons of airborne TWP-derived atmospheric MPs annually in the period 2015-2019, with the highest emissions from passenger cars and heavy-duty vehicles. On average, we found that airborne TWP emissions from passenger cars by country had substantial decreased (up to ∼33%) during COVID-19 lockdowns in 2020 and pronounced increased (by a factor ∼1.9) from vehicle electrification by the next three decades. We conclude that the stunning mass of airborne TWP is a predominant source of atmospheric MP. We underscore the necessity of TWP emissions control among the United States, China, and India. Our findings can be of great use to environmental transportation planners for devising vehicle/tire-oriented decision support tools. Our data offer information to enhance TWP-exposure estimates, to examine long-term exposure trends, and subsequently to improve health risk assessment during pandemic outbreak and future electrification.