A field comparison of volatile organic compound measurements using passive organic vapor monitors and stainless steel canisters.

Concurrent field measurements of 10 volatile organic compounds (VOCs) were made using passive diffusion-based organic vapor monitors (OVMs) and the U.S. Federal Reference Method, which comprises active monitoring with stainless steel canisters (CANs). Measurements were obtained throughout a range of weather conditions, repeatedly over the course of three seasons, and at three different locations in the Minneapolis/St. Paul metropolitan area. Ambient concentrations of most VOCs as measured by both methods were low compared to those of other large metropolitan areas. For some VOCs a considerable fraction of measurements was below the detection limit of one or both methods. The observed differences between the two methods were similar across measurement sites, seasons, and meteorological variables. A Bayesian analysis with uniform priors on the differences was applied, with accommodation of sometimes heavy censoring (nondetection) in either device. The resulting estimates of bias and standard deviation of the OVM relative to the CAN were computed by tertile of the canister-measured concentration. In general, OVM and CAN measurements were in the best agreement for benzene and other aromatic compounds with hydrocarbon additions (ethylbenzene, toluene, and xylenes). The two methods were not in such good agreement for styrene and halogenated compounds (carbon tetrachloride, p-dichlorobenzene, methylene chloride, and trichloroethylene). OVMs slightly overestimated benzene concentrations and carbon tetrachloride at low concentrations, but in all other cases where significant differences were found, OVMs underestimated relative to canisters. Our study indicates that the two methods are in agreement for some compounds, but not all. We provide data and interpretation on the relative performance of the two VOC measurement methods, which facilitates intercomparisons among studies.

Comparing air dispersion model predictions with measured concentrations of VOCs in urban communities.

Air concentrations of nine volatile organic compounds were measured over 48-h periods at 23 locations in three communities in the Minneapolis-St. Paul metropolitan area. Concentrations at the same times and locations were modeled using a standard regulatory air dispersion model (ISCST3). The goal of the study was to evaluate model performance by comparing predictions with measurements using linear regression and estimates of bias. The modeling, done with mobile and area source emissions resolved to the census tract level and characterized as model area sources, represents an improvement over large-scale airtoxics modeling analyses done to date. Despite the resolved spatial scale, the model did not fully capture the spatial resolution in concentrations in an area with a sharp gradient in emissions. In a census tract with a major highway at one end of the tract (i.e., uneven distribution of emissions within the tract), model predictions atthe opposite end of the tract overestimated measured concentrations. This shortcoming was seen for pollutants emitted mainly by mobile sources (benzene, ethylbenzene, toluene, and xylenes). We suggest that major highways would be better characterized as line sources. The model also failed to fully capture the temporal variability in concentrations, which was expected since the emissions inventory comprised annual average values. Based on our evaluation metrics, model performance was best for pollutants emitted mainly from mobile sources and poorest for pollutants emitted mainlyfrom area sources. Important sources of error appeared to be the source characterization (especially location) and emissions quantification. We expect that enhancements in the emissions inventory would give the greatest improvement in results. As anticipated for a Gaussian plume model, performance was dramatically better when compared to measurements that were not matched in space or time. Despite the limitations of our analysis, we found thatthe regulatory air dispersion model was generally able to predict space and time matched 48-h average ambient concentrations of VOC species within a factor of 2 on average, results that meet regulatory model acceptance criteria.