Epidemiological and toxicological studies continue to demonstrate correlative and causal relationships between exposure to traffic-related air pollution and various metrics of adverse pulmonary, cardiovascular, and neurological health effects. The key challenge for in vivo studies is replicating real-world, near-roadway exposure dynamics in laboratory animal models that mimic true human exposures. The advantage of animal models is the accelerated time scales to show statistically significant physiological and/or behavioral response. This work describes a novel exposure facility adjacent to a major freeway tunnel system that provides a platform for real-time chronic exposure studies. The primary conclusion is that particulate matter (PM) concentrations at this facility are routinely well below the National Ambient Air Quality Standards (NAAQS), but studies completed to date still demonstrate significant neurological and cardiovascular effects. Internal combustion engines produce large numbers of ultrafine particles that contribute negligible mass to the atmosphere relative to NAAQS regulated PM but have high surface area and mobility in the body. It is posited here that current federal and state air quality standards are thus insufficient to fully protect human health, most notably the developing and aging brain, due to regulatory gaps for ultrafine particles.
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http://dx.doi.org/10.1021/acs.est.1c07047 | DOI Listing |
Environ Res
January 2025
Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Beer Sheva, Israel.
Air-pollution monitoring is sparse across most of the United States, so geostatistical models are important for reconstructing concentrations of fine particulate air pollution (PM) for use in health studies. We present XGBoost-IDW Synthesis (XIS), a daily high-resolution PM machine-learning model covering the contiguous US from 2003 through 2023. XIS uses aerosol optical depth from satellites and a parsimonious set of additional predictors to make predictions at arbitrary points, capturing near-roadway gradients and allowing the estimation of address-level exposures.
View Article and Find Full Text PDFCurr Environ Health Rep
January 2025
Brandeis University, Waltham, MA, USA.
Purpose Of Review: Indoor air pollution is likely to be elevated in multi-family housing and to contribute to health disparities, but limited studies to date have systematically considered the empirical evidence for exposure differentials between multi-family and single-family housing. Our goal is to separately examine the drivers of residential indoor air pollution, including outdoor air pollution, ventilation and filtration, indoor sources, and occupant activity patterns, using secondhand smoke as a case study to examine the behavioral dimensions of indoor environmental interventions.
Recent Findings: Within studies published from 2018 to 2023, multi-family homes have higher average outdoor air pollution than single-family homes given their more frequent presence in urban and near-roadway settings.
Sci Total Environ
October 2023
University of California, Bourns College of Engineering, Center for Environmental Research and Technology (CE-CERT), 1084 Columbia Avenue, Riverside, CA 92507, USA; Department of Chemical and Environmental Engineering, Bourns College of Engineering, University of California, Riverside, CA 92521, USA. Electronic address:
Environ Sci Technol
October 2024
Department of Environmental Health Sciences, Fielding School of Public Health, University of California, Los Angeles, California 90095, United States.
Sci Total Environ
September 2024
Department of Population and Public Health Sciences, University of Southern California, 1845 N Soto St, Los Angeles, CA, USA; Department of Statistical Sciences and School of the Environment, University of Toronto, Toronto, Ontario, Canada. Electronic address:
Air pollution is a major environmental problem and its monitoring is essential for regulatory purposes, policy making, and protecting public health. However, dense networks of air quality monitoring equipment are prohibitively expensive due to equipment costs, labor requirements, and infrastructure needs. As a result, alternative lower-cost methods that reliably determine air quality levels near potent pollution sources such as freeways are desirable.
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