In 2016, the United Nations declared the need for urgent action to combat the global threat of antimicrobial resistance (AMR). In support of this effort, the pharmaceutical industry has committed to measures aimed at improving the stewardship of antibiotics both within and outside the clinic. Notably, a group of companies collaborated to specifically address concerns related to antibiotic residues being discharged from manufacturing sites. In addition to developing a framework of minimum environmental expectations for antibiotic manufacturers, science‐based receiving water targets were established for antibiotics discharged from manufacturing operations. This paper summarizes the holistic approach taken to derive these targets and includes previously unpublished, company‐generated, environmental toxicity data.
Air quality models are typically used to predict the fate and transport of air emissions from industrial sources to comply with federal and state regulatory requirements and environmental standards, as well as to determine pollution control requirements. For many years, the U.S. Environmental Protection Agency (EPA) widely used the Industrial Source Complex (ISC) model because of its broad applicability to multiple source types. Recently, EPA adopted a new rule that replaces ISC with AERMOD, a state-of-the-practice air dispersion model, in many air quality impact assessments. This study compared the two models as well as their enhanced versions that incorporate the Plume Rise Model Enhancements (PRIME) algorithm. PRIME takes into account the effects of building downwash on plume dispersion. The comparison used actual point, area, and volume sources located on two separate facilities in conjunction with site-specific terrain and meteorological data. The modeled maximum total period average ground-level air concentrations were used to calculate potential health effects for human receptors. The results show that the switch from ISC to AERMOD and the incorporation of the PRIME algorithm tend to generate lower concentration estimates at the point of maximum ground-level concentration. However, the magnitude of difference varies from insignificant to significant depending on the types of the sources and the site-specific conditions. The differences in human health effects, predicted using results from the two models, mirror the concentrations predicted by the models.
Recently, intense attention has been given to children's health issues, particularly in the use of consumer products. Because of this attention, researchers have been planning and initiating studies specifically aimed at developing both toxicology data and exposure data directed to improve our understanding of industrial and consumer product chemical impacts on children's health. To ensure that this research is focused on the highest priority chemicals, we present a methodology for determining and prioritizing the higher hazard chemicals and scenarios for which children could be disproportionately or highly exposed. This tiered approach includes a screening step for initial chemical selection, a hazard assessment based on no- or lowest-observed-adverse-effect levels, and a margin of exposure (MOE) calculation. The initial chemical screen focuses on the chemical presence in specific media that are special to children, such as foods children regularly eat and drink, residential or school air, products children use, and soil and dust in and around residences. Data from the literature or from models serve as the initial exposure estimate. This methodology would allow us to focus on those chemicals to which children are most exposed that are also associated with, potentially, the highest risk. Use of the MOE calculation allows for comparison among chemicals, prioritization of chemicals for evaluation and testing, and identification of significant data gaps.
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