Numerical Simulations of Synthetic Ester Hydrolysis in the Indoor Environment.

The hydrolysis of synthetic esters (SEs), including phthalates and adipates, in damp indoor environments can lead to the release of volatile organic compounds implicated in poor air quality and acute health impacts, known as "sick building syndrome" (SBS). We have adapted the multiphase atmospheric chemistry box model, GAMMA, to simulate SE hydrolysis occurring in surface films in the indoor environment, along with multilayer boundary layer mass transfer and ventilation, in order to investigate this phenomenon on a process level. We then applied the model to analyze three scenarios in which hydrolysis has been hypothesized to have a significant impact on indoor air quality. Simulation results suggest that (1) alkaline hydrolysis of bis(2-ethylhexyl) adipate (DEHA) and bis(2-ethylhexyl) phthalate (DEHP) from PVC flooring on damp surfaces alone is not sufficient to explain the levels of 2-ethylhexanol reported in indoor air during episodes of SBS; (2) acute exposure to 2,2,4-trimethyl-1,3-pentanediol (TMPD) may be of concern during and shortly after the application of latex paint on an alkaline surface; and (3) alkaline hydrolysis of SEs following their airborne uptake in aqueous films is not expected to generate considerable amounts of alcohols associated with SBS.

Room-level ventilation in schools and universities.

Ventilation is of primary concern for maintaining healthy indoor air quality and reducing the spread of airborne infectious disease, including COVID-19. In addition to building-level guidelines, increased attention is being placed on room-level ventilation. However, for many universities and schools, ventilation data on a room-by-room basis are not available for classrooms and other key spaces. We present an overview of approaches for measuring ventilation along with their advantages and disadvantages. We also present data from recent case studies for a variety of institutions across the United States, with various building ages, types, locations, and climates, highlighting their commonalities and differences, and examples of the use of this data to support decision making.