Alice Grgicak-Mannion

Spatial Variability and Application of Ratios between BTEX in Two Canadian Cities

Spatial monitoring campaigns of volatile organic compounds were carried out in two similarly sized urban industrial cities, Windsor and Sarnia, ON, Canada. For Windsor, data were obtained for all four seasons at approximately 50 sites in each season (winter, spring, summer, and fall) over a three-year period (2004, 2005, and 2006) for a total of 12 sampling sessions. Sampling in Sarnia took place at 37 monitoring sites in fall 2005. In both cities, passive sampling was done using 3M 3500 organic vapor samplers. This paper characterizes benzene, toluene, ethylbenzene, o, and (m + p)-xylene (BTEX) concentrations and relationships among BTEX species in the two cities during the fall sampling periods. BTEX concentration levels and rank order among the species were similar between the two cities. In Sarnia, the relationships between the BTEX species varied depending on location. Correlation analysis between land use and concentration ratios showed a strong influence from local industries. Use one of the ratios between the BTEX species to diagnose photochemical age may be biased due to point source emissions, for example, 53 tonnes of benzene and 86 tonnes of toluene in Sarnia. However, considering multiple ratios leads to better conclusions regarding photochemical aging. Ratios obtained in the sampling campaigns showed significant deviation from those obtained at central monitoring stations, with less difference in the (m + p)/E ratio but better overall agreement in Windsor than in Sarnia.

Development of temporally refined land-use regression models predicting daily household-level air pollution in a panel study of lung function among asthmatic children

Regulatory monitoring data and land-use regression (LUR) models have been widely used for estimating individual exposure to ambient air pollution in epidemiologic studies. However, LUR models lack fine-scale temporal resolution for predicting acute exposure and regulatory monitoring provides daily concentrations, but fails to capture spatial variability within urban areas. This study coupled LUR models with continuous regulatory monitoring to predict daily ambient nitrogen dioxide (NO2) and particulate matter (PM2.5) at 50 homes in Windsor, Ontario. We compared predicted versus measured daily outdoor concentrations for 5 days in winter and 5 days in summer at each home. We also examined the implications of using modeled versus measured daily pollutant concentrations to predict daily lung function among asthmatic children living in those homes. Mixed effect analysis suggested that temporally refined LUR models explained a greater proportion of the spatial and temporal variance in daily household-level outdoor NO2 measurements compared with daily concentrations based on regulatory monitoring. Temporally refined LUR models captured 40% (summer) and 10% (winter) more of the spatial variance compared with regulatory monitoring data. Ambient PM2.5 showed little spatial variation; therefore, daily PM2.5 models were similar to regulatory monitoring data in the proportion of variance explained. Furthermore, effect estimates for forced expiratory volume in 1 s (FEV1) and peak expiratory flow (PEF) based on modeled pollutant concentrations were consistent with effects based on household-level measurements for NO2 and PM2.5. These results suggest that LUR modeling can be combined with continuous regulatory monitoring data to predict daily household-level exposure to ambient air pollution. Temporally refined LUR models provided a modest improvement in estimating daily household-level NO2 compared with regulatory monitoring data alone, suggesting that this approach could potentially improve exposure estimation for spatially heterogeneous pollutants. These findings have important implications for epidemiologic studies — in particular, for research focused on short-term exposure and health effects.

The influence of neighborhood traffic density on the respiratory health of elementary schoolchildren.

BACKGROUND Several studies have found that living near major roadways is associated with an increase in respiratory illness but few studies have measured the volume and type of traffic. OBJECTIVE We investigated the relation between traffic volume and respiratory health of 2328 children 9 to 11 years old in the city of Windsor, Canada. METHODS We identified the roadways within a 200 meter radius of the childs neighborhood using the latitude and longitude of the residential postal code. Traffic exposure was defined as the sum of the annual volume of vehicles on all of these roadways. Volume was calculated using sensors to detect passing vehicles (simple traffic counts), and by counts and direction of traffic at intersections (turning movement counts). Ventilatory lung function was measured by spirometry and airway inflammation by exhaled nitric oxide (eNO). RESULTS The odds ratio between an interquartile increase in truck turning movement counts and chest congestion was 1.20 (1.06-1.35). The percentage of predicted FVC declined 0.68%, (95% CI 1.32, 0.03) for an interquartile increase in simple traffic counts (33,787 vehicles daily). Among those with self-reported asthma, effect sizes were larger. Percentage predicted FEV(1) declined 1.84% (95% CI 0.07, 3.61) associated with an interquartile range increase in turning movement counts. No statistically significant change was detected between traffic measures and exhaled nitric oxide. CONCLUSIONS Our findings provide further support for the hypothesis that neighborhood exposure to traffic-related air pollution increases respiratory symptoms and reduces ventilatory function in children, especially those with self-reported asthma.

Establishing the spatial variability of ambient nitrogen dioxide in Windsor, Ontario

This study is aimed at identifying the determinants of intra‐urban variation in ambient concentrations of nitrogen dioxide (NO2) in Windsor, Ontario, Canada, and to develop a model to predict NO2 in the city. NO2 samples were collected over a two‐week period during winter 2004 by using passive samplers in 50 locations across Windsor. A land use regression (LUR) model was constructed to generate independent variables that could best predict NO2 concentrations across the city. We tested 71 variables of land use, traffic, road characteristics, population and dwelling counts, and physical geographic variables such as elevation. The final model contained five variables: distance to the Ambassador Bridge, daily traffic on Class 1 and Class 2 arterial roads within 400 m, industry within 600 m, and total population within 700 m. All the variables were statistically significant and had the expected direction of correlation. The final regression model yielded a coefficient of determination, R 2, of 0.88. The spatial variations captured in this analysis are being used to guide the selection of participants for a number of Health Canada studies.

Variable δ15N Diet-Tissue Discrimination Factors among Sharks: Implications for Trophic Position, Diet and Food Web Models

The application of stable isotopes to characterize the complexities of a species foraging behavior and trophic relationships is dependent on assumptions of δ15N diet-tissue discrimination factors (∆15N). As ∆15N values have been experimentally shown to vary amongst consumers, tissues and diet composition, resolving appropriate species-specific ∆15N values can be complex. Given the logistical and ethical challenges of controlled feeding experiments for determining ∆15N values for large and/or endangered species, our objective was to conduct an assessment of a range of reported ∆15N values that can hypothetically serve as surrogates for describing the predator-prey relationships of four shark species that feed on prey from different trophic levels (i.e., different mean δ15N dietary values). Overall, the most suitable species-specific ∆15N values decreased with increasing dietary-δ15N values based on stable isotope Bayesian ellipse overlap estimates of shark and the principal prey functional groups contributing to the diet determined from stomach content analyses. Thus, a single ∆15N value was not supported for this speciose group of marine predatory fishes. For example, the ∆15N value of 3.7‰ provided the highest percent overlap between prey and predator isotope ellipses for the bonnethead shark (mean diet δ15N = 9‰) whereas a ∆15N value < 2.3‰ provided the highest percent overlap between prey and predator isotope ellipses for the white shark (mean diet δ15N = 15‰). These data corroborate the previously reported inverse ∆15N-dietary δ15N relationship when both isotope ellipses of principal prey functional groups and the broader identified diet of each species were considered supporting the adoption of different ∆15N values that reflect the predators’ δ15N-dietary value. These findings are critical for refining the application of stable isotope modeling approaches as inferences regarding a species’ ecological role in their community will be influenced with consequences for conservation and management actions.

Assessment of decadal changes in sediment contamination in a large connecting channel (Detroit River, North America).

Concentrations of selected heavy metals (Cd, Cu, Hg, Pb, Zn) and organic contaminants (PCBs, PAHs) were investigated in samples from the Detroit River (Great Lakes, North America) in 1999 and 2008/09 collected using a stratified random sampling design. Getis-Ord geospatial analysis was used to further establish locations of areas demonstrating significantly high and low contaminant concentrations in the river. Based on the stratified random sampling design, a majority of the examined metals and organic contaminants demonstrated little or no trends with respect to regional sediment concentrations and river-wide mass balances over the investigated time interval. The Getis-Ord analysis revealed local scales of contaminated and clean areas which did not conform to the original strata used in the geostatistical sampling design. It is suggested that geospatial analyses such as Getis-Ord be used in the design of future sediment quality surveys to refine locations of strata that can simultaneously address sediment recovery over system-wide, regional and local spatial scales.

Possible Ballast Water Transfer of Lionfish to the Eastern Pacific Ocean

The Indo-Pacific Red Lionfish was first reported off the Florida coast in 1985, following which it has spread across much of the SE USA, Gulf of Mexico, and Caribbean Sea. Lionfish negatively impact fish and invertebrate assemblages and abundances, thus further spread is cause for concern. To date, the fish has not been reported on the Pacific coast of North or Central America. Here we examine the possibility of ballast water transfer of lionfish from colonized areas in the Atlantic Ocean to USA ports on the Pacific coast. Over an eight-year period, we documented 27 commercial vessel-trips in which ballast water was loaded in colonized sites and later discharged untreated into Pacific coast ports in the USA. California had the highest number of discharges including San Francisco Bay and Los Angeles-Long Beach. A species distribution model suggests that the probability of lionfish establishment is low for the western USA, Colombia and Panama, low to medium for Costa Rica, Nicaragua, El Salvador and Guatemala, medium to high for mainland Ecuador, and very high for western Mexico, Peru and the Galapagos Islands. Given the species’ intolerance of freshwater conditions, we propose that ballast water exchange be conducted in Gatún Lake, Panama for western-bound vessels carrying ‘risky’ ballast water to prevent invasion of the eastern Pacific Ocean.

Assessment of hazard metrics for predicting field benthic invertebrate toxicity in the Detroit River, Ontario, Canada

ABSTRACT Numerical sediment quality guidelines (SQGs) are frequently used to interpret site‐specific sediment chemistry and predict potential toxicity to benthic communities. These SQGs are useful for a screening line of evidence (LOE) that can be combined with other LOEs in a full weight of evidence (WOE) assessment of impacted sites. Three common multichemical hazard quotient methods (probable effect concentration [PEC]‐Qavg, PEC‐Qmet, and PEC‐Qsum) and a novel (hazard score [HZD]) approach were used in conjunction with a consensus‐based set of SQGs to evaluate the ability of different scoring metrics to predict the biological effects of sediment contamination under field conditions. Multivariate analyses were first used to categorize river sediments into distinct habitats based on a set of physicochemical parameters to include gravel, low and high flow sand, and silt. For high flow sand and gravel, no significant dose–response relationships between numerically dominant species and various toxicity metric scores were observed. Significant dose–response relationships were observed for chironomid abundances and toxicity scores in low flow sand and silt habitats. For silt habitats, the HZD scoring metric provided the best predictor of chironomid abundances compared to various PEC‐Q methods according to goodness‐of‐fit tests. For low flow sand habitats, PEC‐Qsum followed by HZD, provided the best predictors of chironomid abundance. Differences in apparent chironomid toxicity between the 2 habitats suggest habitat‐specific differences in chemical bioavailability and indicator taxa sensitivity. Using an IBI method, the HZD, PEC‐Qavg, and PEC‐Qmet approaches provided reasonable correlations with calculated IBI values in both silt and low flow sand habitats but not for gravel or high flow sands. Computation differences between the various multi‐chemical toxicity scoring metrics and how this contributes to bias in different estimates of chemical mixture toxicity scores are discussed and compared. Integr Environ Assess Manag 2017;13:410–422.