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This study investigates air pollutant concentrations across the international airshed spanning Detroit, Michigan, USA and Windsor, Ontario, Canada. The Geospatial Determinants of Health Outcomes Consortium (GeoDHOC) measured air quality concurrently in Detroit and Windsor using consistent sampling methods and locations during separate, two-week periods in September 2008 and May/June 2009. This paper presents 2009 results and compares them to previously reported 2008 campaign results to assess spatial and temporal variability. A high-density array of 100 passive and 50 active samplers was used to measure nitrogen dioxide (NO2), 26 volatile organic compounds (VOCs), 23 polycyclic aromatic hydrocarbons (PAHs), and three size fractions of particulate matter (PM) in both campaigns. Geospatial and non-spatial tools were used to investigate changes in concentration distributions and site classification into low/medium/high tertiles between the campaigns. During the two-week 2009 campaign, general pollution patterns remained consistent with those observed during 2008. Higher concentrations in Detroit, strong correlations amongst the BTEX group, and consistency of sites falling into the low and high tertiles were observed. Similar spatial patterns for NO2, VOCs, BTEX, and PAHs were also found during both campaigns. Conversely, PM1-2.5 and PM2.5-10 distributions showed greater variability, as did toluene/benzene ratios. Observed differences are attributable to changes in point source emissions associated with changes in localized activities, possibly related to decreased economic and industrial activity in response to the downturn that began in late 2008. Repeated sampling at multiple locations is important to determine spatial and temporal variability in absolute concentrations. However, if the definition of relatively high and low concentrations regions within a well-established urban area is adequate to estimate future air pollutant exposures, a single multi-location campaign may suffice.

High density air monitoring campaigns provide spatial patterns of pollutant concentrations which are integral in exposure assessment. Such analysis can assist with the determination of links between air quality and health outcomes, however, problems due to missing data can threaten to compromise these studies. This research evaluates four methods; mean value imputation, inverse distance weighting (IDW), inter-species ratios, and regression, to address missing spatial concentration data ranging from one missing data point up to 50% missing data. BTEX (benzene, toluene, ethylbenzene, and xylenes) concentrations were measured in Windsor and Sarnia, Ontario in the fall of 2005. Concentrations and inter-species ratios were generally similar between the two cities. Benzene (B) was observed to be higher in Sarnia, whereas toluene (T) and the T/B ratios were higher in Windsor. Using these urban, industrialized cities as case studies, this research demonstrates that using inter-species ratios or regression of the data for which there is complete information, along with one measured concentration (i.e. benzene) to predict for missing concentrations (i.e. TEX) results in good agreement between predicted and measured values. In both cities, the general trend remains that best agreement is observed for the leave-one-out scenario, followed by 10% and 25% missing, and the least agreement for the 50% missing cases. In the absence of any known concentrations IDW can provide reasonable agreement between observed and estimated concentrations for the BTEX species, and was superior over mean value imputation which was not able to preserve the spatial trend. The proposed methods can be used to fill in missing data, while preserving the general characteristics and rank order of the data which are sufficient for epidemiologic studies.

An air quality monitoring study focusing on spatial patterns was carried out in the urban industrial city of Windsor, Ontario, Canada (42.267°N, 82.95°W). This study took place over a three-year period (2004–2006), during all four seasons for a total of 12 two-week sampling periods (each with approximately 50 sites) at 162 sites across the city. Benzene, toluene, ethylbenzene, (m + p)-xylene, and o-xylene (BTEX) were measured using 3M #3500 Organic Vapor Samples (Guillevan, Montreal). Results from this investigation indicate that significant variability is present temporally (seasonally and annually) and spatially. The three-year mean concentrations in μg m−3 were: benzene (0.76), toluene (2.75), ethylbenzene (0.45), o-xylene (0.47), (m + p)-xylene (1.36), and total BTEX (5.64), with greater variability within each year compared with variability between the three years. Concentrations were highly correlated between most BTEX species, consistent with previous studies in urban areas. Toluene to benzene ratios were consistent between years, with the highest observed ratios occurring in summer, the lowest in winter, and fall and spring values falling in between. The range of ratios suggests that the majority of these two compounds originate from mobile emissions. (m + p)-Xylene to ethylbenzene ratios, used as indicators of photochemical age, showed a three-year mean of 3.0 with little spatial and temporal variability suggesting that relatively fresh and homogenous sources of these species are present in this area. The seasonal trends across the spatial network were representative of the seasonal patterns obtained at a long term monitoring station, with both methods indicating that fall and spring concentrations were preferred proxies of annual means. However, significant spatial variability of concentrations was observed. The upper range of concentrations compared with the values obtained at the central monitoring station differed by up to a factor of six, highlighting the importance of multiple sampling sites to reduce exposure misclassification. Significant correlations between seasons were observed in all three years, revealing a consistent rank order of high to low concentrations among the monitoring sites within a given year. Consideration of all analyses suggests that when resources are limited to a single sampling season, fall and spring mean values for concentrations and ratios seem to best represent the annual average in this city. Other study design consideration suggestions are also provided for future air quality research.

Dept. of Civil and Environmental Engineering, University of Windsor, Windsor, Ontario, Canada Dept. of Geology, Wayne State University, 0224 Old Main, 4841 Cass, Detroit, MI 48202, USA Air Health Science Division, Health Canada, Ottawa, Ontario, Canada Dept. of Family Medicine, Wayne State University, Detroit, MI, USA Great Lakes Institute for Environmental Research, University of Windsor, Windsor, Ontario, Canada Henry Ford Health System, Detroit, MI, USA College of Nursing, Wayne State University, Detroit, MI, USA h School of Nursing, Eastern Michigan University, Ypsilanti, MI, USA i Institute of Environmental Health Sciences, Wayne State University, Detroit, MI, USA

As part of a larger research project initiated by the Geospatial Determinants of Health Outcomes Consortium (GeoDHOC), an air quality study was conducted in an international airshed encompassing Detroit, Michigan, USA, and Windsor, Ontario, Canada. Active and passive samplers were used to measure nitrogen dioxide (NO2), sulfur dioxide (SO2), 26 volatile organic compounds (VOCs), 23 polycyclic aromatic hydrocarbons (PAHs) and pesticides, and three size fractions of particulate matter (PM) over a two-week period in September, 2008. Measurements of NO2 and 14 VOCs were found to be acceptable at 98 out of 100 passive monitoring sites. PAH and PM measurements were acceptable at 38 out of 50 active sites. Mean concentrations for all analytes except for PM2.5–10 were higher in Detroit than Windsor by a factor of up to 1.8. Strong statistical correlations were found among benzene, toluene, ethylbenzene, and xylene (BTEX), as well as between NO2 and PM in Detroit. In Windsor, the strongest correlations were between NO2 and total VOCs, as well as total PAHs and total VOCs. Differences in the degree of correlation observed in Detroit and Windsor are attributable to differences in the volume and composition of emissions within the two cities. Spatial variability was evaluated using a combination of statistical (coefficient of variation) and geostatistical (standardized variogram slope) metrics together with concentration maps. Greater spatial variability was observed for total VOCs and total BTEX in Detroit, while greater variability of NO2, total PAHs, and PM was found in Windsor. Results of this study suggest that statistical correlations between NO2 and other contaminants may not provide sufficient justification for the indiscriminant use of NO2 as a proxy for those contaminants if smaller scale features are to be reproduced.