ABSTRACT Bacteria within the genus Mycobacterium can be abundant in showerheads, and the inhalation of aerosolized mycobacteria while showering has been implicated as a mode of transmission in nontuberculous mycobacterial (NTM) lung infections. Despite their importance, the diversity, distributions, and environmental predictors of showerhead-associated mycobacteria remain largely unresolved. To address these knowledge gaps, we worked with citizen scientists to collect showerhead biofilm samples and associated water chemistry data from 656 households located across the United States and Europe. Our cultivation-independent analyses revealed that the genus Mycobacterium was consistently the most abundant genus of bacteria detected in residential showerheads, and yet mycobacterial diversity and abundances were highly variable. Mycobacteria were far more abundant, on average, in showerheads receiving municipal water than in those receiving well water and in U.S. households than in European households, patterns that are likely driven by differences in the use of chlorine disinfectants. Moreover, we found that water source, water chemistry, and household location also influenced the prevalence of specific mycobacterial lineages detected in showerheads. We identified geographic regions within the United States where showerheads have particularly high abundances of potentially pathogenic lineages of mycobacteria, and these “hot spots” generally overlapped those regions where NTM lung disease is most prevalent. Together, these results emphasize the public health relevance of mycobacteria in showerhead biofilms. They further demonstrate that mycobacterial distributions in showerhead biofilms are often predictable from household location and water chemistry, knowledge that advances our understanding of NTM transmission dynamics and the development of strategies to reduce exposures to these emerging pathogens. IMPORTANCE Bacteria thrive in showerheads and throughout household water distribution systems. While most of these bacteria are innocuous, some are potential pathogens, including members of the genus Mycobacterium that can cause nontuberculous mycobacterial (NTM) lung infection, an increasing threat to public health. We found that showerheads in households across the United States and Europe often harbor abundant mycobacterial communities that vary in composition depending on geographic location, water chemistry, and water source, with households receiving water treated with chlorine disinfectants having particularly high abundances of certain mycobacteria. The regions in the United States where NTM lung infections are most common were the same regions where pathogenic mycobacteria were most prevalent in showerheads, highlighting the important role of showerheads in the transmission of NTM infections.
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This content will become publicly available on December 1, 2024
High resolution synthetic residential energy use profiles for the United States
Abstract Efficient energy consumption is crucial for achieving sustainable energy goals in the era of climate change and grid modernization. Thus, it is vital to understand how energy is consumed at finer resolutions such as household in order to plan demand-response events or analyze impacts of weather, electricity prices, electric vehicles, solar, and occupancy schedules on energy consumption. However, availability and access to detailed energy-use data, which would enable detailed studies, has been rare. In this paper, we release a unique, large-scale, digital-twin of residential energy-use dataset for the residential sector across the contiguous United States covering millions of households. The data comprise of hourly energy use profiles for synthetic households, disaggregated into Thermostatically Controlled Loads (TCL) and appliance use. The underlying framework is constructed using a bottom-up approach. Diverse open-source surveys and first principles models are used for end-use modeling. Extensive validation of the synthetic dataset has been conducted through comparisons with reported energy-use data. We present a detailed, open, high resolution, residential energy-use dataset for the United States.
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- NSF-PAR ID:
- 10403932
- Date Published:
- Journal Name:
- Scientific Data
- Volume:
- 10
- Issue:
- 1
- ISSN:
- 2052-4463
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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