Mongolia has the lowest population density of any country, yet its population centers experience poor wintertime air quality because the cold climate drives strong ground-level inversions and pervasive solid fuels use for distributed residential space heating. Ulaanbaatar (UB, pop. ~1.5MM) has robust air monitoring but measurements outside of UB are sparse. Through a partnership with UNICEF Mongolia, air quality measurements are being conducted to quantify PM2.5 spatiotemporal variability in Bayankhongor (BKH, pop.~30K) and assess children’s PM2.5 exposures in kindergartens, maternity wards, and pediatric hospitals in both BKH and UB. Science collaborators include the Mongolian University of Science and Technology and University of California, Irvine. [Funding: UNICEF Mongolia] More details…
Green Heart Louisville is being conducted in collaboration with University of Louisville Envirome Institute (Aruni Bhatnagar, Project PI) and numerous other partners. It is a first-of-its-kind scientific experiment to test if increasing green space in a neighborhood will improve air quality and human health. We are studying how Louisville’s tree canopy affects heart health and risk for developing diabetes and obesity. Researchers will investigate new ways to prevent heart disease, diabetes, and obesity and develop a scientifically backed “greenprint” for creating healthier cities. Our group is leading the environmental monitoring including air quality (passive sampling and mobile platform measurements), noise, and greenness metrics. [Funding: NIH and the The Nature Conservancy]
As a follow-up to the Louisville Green for Good project, we conduting a detailed characterization of an engineered vegetative buffer installed next to an arterial roadway. The goals are to: quantify the buffer’s efficacy to reduce near-road air pollution; and to develop modeling tools to optimize buffer design. Our group is leading the measurments which include two-week integrated passive sampling for NO and NOx, and mobile platform measurments at one second time resolution for high ultrafine particle (UFP) number concentration. Computation fluid dynamics (CFD) modeling is being conducted by the Max Zhang group at Cornell University. Other science collabortors, providing in-kind support, include the Hyphae Design Group and the University of Louisville. [Funding: FHWA/DOT and the Institute for Healthy Air, Water and Soil]
As part of the University of Louisville Superfund Research Program (Sanjay Srivastava, Center PI), we are leading a project to: develop a new instrument to measure volatile organic compounds (VOCs) at high time resolution; and conduct mobile platform measurements and land use regression modeling to map VOCs on urban- and neighborhood-scales. The Brent Williams group (Washington University in St. Louis) is leading the instrument development. Nathan Kreisberg (Aerosol Dyanmics, Inc.) is advising on the instrument development, Jason Su (University of California-Berkeley) and Steve Hankey (Virginia Tech) are collaborating on the field studies design and data analysis, and Russ Barnett (University of Louisville) is advising on the field study logistics. [Funding: NIH]
The SMELTER project is conducted in collaboration with Washington University School of Medicine (Brad Racette, Project PI) and the University of the Witwatersrand in Johannesburg, South Africa. Manganese (Mn) is an established neurotoxicant with complex pharmacology, due to its role as an essential trace element. This project builds on a large body of research generated by the Racette Group over the last decade that demonstrated Mn-exposed welders have a high prevalence of parkinsonism compared to a reference population. In this project, we are performing a population-based epidemiology study of Mn-exposed adults living near a large Mn smelter in Meyerton, South Africa, in which we compare the prevalence and severity of motor, cognitive control, and mood dysfunction across the community which has differential exposures. [Funding: NIH]
Various ongoing and recent projects have assessed spatiotemporal variability of ambient particulate matter and other air quality parameters within various airsheds (Hong Kong, Detroit, St. Louis, Louisville). Special emphasis is placed on characterizing measurement error and how it might confound the interpretation of common metrics for spatial and temporal variability, and on using data-driven approaches to identify emission sources that are typically not resolved by source apportionment models.