BTEX exposures in an area impacted by industrial and mobile sources: Source attribution and impact of averaging time

ABSTRACT

The impacts of emissions plumes from major industrial sources on black carbon (BC) and BTEX (benzene, toluene, ethyl benzene, xylene isomers) exposures in communities located >10 km from the industrial source areas were identified with a combination of stationary measurements, source identification using positive matrix factorization (PMF), and dispersion modeling. The industrial emissions create multihour plume events of BC and BTEX at the measurement sites. PMF source apportionment, along with wind patterns, indicates that the observed pollutant plumes are the result of transport of industrial emissions under conditions of low boundary layer height. PMF indicates that industrial emissions contribute >50% of outdoor exposures of BC and BTEX species at the receptor sites. Dispersion modeling of BTEX emissions from known industrial sources predicts numerous overnight plumes and overall qualitative agreement with PMF analysis, but predicts industrial impacts at the measurement sites a factor of 10 lower than PMF. Nonetheless, exposures associated with pollutant plumes occur mostly at night, when residents are expected to be home but are perhaps unaware of the elevated exposure. Averaging data samples over long times typical of public health interventions (e.g., weekly or biweekly passive sampling) misapportions the exposure, reducing the impact of industrial plumes at the expense of traffic emissions, because the longer samples cannot resolve subdaily plumes. Suggestions are made for ways for future distributed pollutant mapping or intervention studies to incorporate high time resolution tools to better understand the potential impacts of industrial plumes.

Implications: Emissions from industrial or other stationary sources can dominate air toxics exposures in communities both near the source and in downwind areas in the form of multihour plume events. Common measurement strategies that use highly aggregated samples, such as weekly or biweekly averages, are insensitive to such plume events and can lead to significant under apportionment of exposures from these sources.

Additional information

Funding

This work was funded by the Heinz Endowments under grant E2033. The authors thank Jason Maranche of the Allegheny County Health Department for assistance with AERMOD, and Marie Kelly of the Allegheny County Health Department for assistance with the emissions inventory data for Allegheny County.

Notes on contributors

Albert A. Presto

Albert A. Presto is an Assistant Research Professor in the Department of Mechanical Engineering and the Center for Atmospheric Particle Studies at Carnegie Mellon.

Timothy R. Dallmann

Timothy R. Dallmann was a postdoc in Dr. Presto’s group and is now with the International Council on Clean Transit in Washington, DC.

Peishi Gu

Peishi Gu is a Ph.D. student and Unnati Rao was a master’s student in Dr. Presto’s group. Unnati Rao is now a student at the University of California-Riverside, Department of Chemical Engineering.

Unnati Rao

Peishi Gu is a Ph.D. student and Unnati Rao was a master’s student in Dr. Presto’s group. Unnati Rao is now a student at the University of California-Riverside, Department of Chemical Engineering.