Windsor, Ontario exposure assessment study: design and methods validation of personal, indoor, and outdoor air pollution monitoring

The Windsor, Ontario Exposure Assessment Study evaluated the contribution of ambient air pollutants to personal and indoor exposures of adults and asthmatic children living in Windsor, Ontario, Canada. In addition, the role of personal, indoor, and outdoor air pollution exposures upon asthmatic children's respiratory health was assessed. Several active and passive sampling methods were applied, or adapted, for personal, indoor, and outdoor residential monitoring of nitrogen dioxide, volatile organic compounds, particulate matter (PM; PM-2.5 pm [PM2.5] and < or =10 microm [PM10] in aerodynamic diameter), elemental carbon, ultrafine particles, ozone, air exchange rates, allergens in settled dust, and particulate-associated metals. Participants completed five consecutive days of monitoring during the winter and summer of 2005 and 2006. During 2006, in addition to undertaking the air pollution measurements, asthmatic children completed respiratory health measurements (including peak flow meter tests and exhaled breath condensate) and tracked respiratory symptoms in a diary. Extensive quality assurance and quality control steps were implemented, including the collocation of instruments at the National Air Pollution Surveillance site operated by Environment Canada and at the Michigan Department of Environmental Quality site in Allen Park, Detroit, MI. During field sampling, duplicate and blank samples were also completed and these data are reported. In total, 50 adults and 51 asthmatic children were recruited to participate, resulting in 922 participant days of data. When comparing the methods used in the study with standard reference methods, field blanks were low and bias was acceptable, with most methods being within 20% of reference methods. Duplicates were typically within less than 10% of each other, indicating that study results can be used with confidence. This paper covers study design, recruitment, methodology, time activity diary, surveys, and quality assurance and control results for the different methods used.     

Triclosan in individual human milk samples from Australia

Triclosan is a chlorinated phenol ether that has been in widespread use as a broad-spectrum antibacterial agent for four decades. When compared to the limited international data available on human body burden of triclosan, results from a pooled blood study suggested that triclosan concentrations in Australia were a factor two higher than observed in Sweden. This study determined triclosan levels in individual human milk samples (n = 151) collected between 2002 and 2005 from primiparous Australian mothers. It provided the first report of population triclosan levels and individual variation in Australia and gave a measure of infant exposure via breast feeding. The distribution of triclosan concentration was positively skewed, with 7.2% of the samples below the LOQ, 66% with a concentration of less than or equal to 1.0 ng g⁻¹ fresh weight and the remaining samples above 1 ng g⁻¹ reaching a maximum concentration of 19 ng g⁻¹ fresh weight. The mean and median triclosan concentrations were 1.3 ± 2.7 ng g⁻¹ f.w. and 0.26 ng g⁻¹ f.w., respectively. The results of this study showed high variability in triclosan concentrations between individuals and no correlations with maternal age (p = 0.094), maternal weight (p = 0.971) or infant age at the time of sample collection (p = 0.621). A large number of samples contained low or non-quantifiable concentrations of triclosan and so, in Australia, ubiquitous background exposure due to environmental sources is low. This means that body burden can be influenced by an individual’s use of triclosan containing product. Given that triclosan containing product use is continuing, it is important that monitoring in both humans and the environment is continued and that triclosan containing products are adequately labeled so that an individual can choose to avoid exposure.     

Heavy metal (Cu, Zn, Cd and Pb) contamination of vegetables in urban India: a case study in Varanasi

The contributions of heavy metals in selected vegetables through atmospheric deposition were quantified in an urban area of India. Deposition rate of Zn was recorded maximum followed by Cu, Cd and Pb. The concentrations of Zn and Cu were highest in Brassica oleracea, Cd in Abelmoschus esculentus and B. oleracea, while Pb was highest in Beta vulgaris. Heavy metal pollution index showed that B. oleracea was maximally contaminated with heavy metals followed by A. esculentus and then B. vulgaris. The results of washing showed that atmospheric deposition has contributed to the increased levels of heavy metals in vegetables. Both Cu and Cd posed health risk to local population via test vegetables consumption, whereas Pb posed the same only through B. oleracea. The study concludes that atmospheric depositions can elevate the levels of heavy metals in vegetables during marketing having potential health hazards to consumers.     

The impacts of knowledge of the past on preferences for future landscape change

In this paper, we investigate whether people's knowledge of the past influences their preferences and values towards future landscape change. "Knowledge of the past" is one aspect of the information set held by individuals, and a well-established finding in economics is that changes in information can change preferences and values. The particular aspects of knowledge of the past we work with here are: (i) awareness of past landuse, as represented by woodland cover and (ii) awareness of differing and sometimes contradictory literary impressions of this past landscape. The case studies used here relate to prospective changes in woodland cover in two UK national parks, the Lake District and the Trossachs. We find that people who are made aware that the landscape has changed over time, or that perceptions of the landscape have changed over time, are more likely to favour changes to the current landscape (are less likely to favour the status quo). Knowledge of the past therefore seems to have an impact on preferences for future landscapes. We also investigate the impacts on preferences of how "special", how "wild" and how "worked in" people perceive the landscapes of these two national parks to be.     

A statistical assessment of saturation and mobile sampling strategies to estimate long-term average concentrations across urban areas

The objectives of this study were: (1) to quantify the errors associated with saturation air quality monitoring in estimating the long-term (i.e., annual and 5 yr) mean at a given site from four 2-week measurements, once per season; and (2) to develop a sampling strategy to guide the deployment of mobile air quality facilities for characterizing intraurban gradients of air pollutants, that is, to determine how often a given location should be visited to obtain relatively accurate estimates of the mean air pollutant concentrations. Computer simulations were conducted by randomly sampling ambient monitoring data collected in six Canadian cities at a variety of settings (e.g., population-based sites, near-roadway sites). The 5-yr (1998-2002) dataset consisted of hourly measurements of nitric oxide (NO), nitrogen dioxide (NO2), oxides of nitrogen (NOx), sulfur dioxide (SO2), coarse particulate matter (PM10), fine particulate matter (PM2.5), and CO. The strategy of randomly selecting one 2-week measurement per season to determine the annual or long-term average concentration yields estimates within 30% of the true value 95% of the time for NO2, PM10 and NOx. Larger errors, up to 50%, are expected for NO, SO2, PM2.5, and CO. Combining concentrations from 85 random 1-hr visits per season provides annual and 5-yr average estimates within 30% of the true value with good confidence. Overall, the magnitude of error in the estimates was strongly correlated with the variability of the pollutant. A better estimation can be expected for pollutants known to be less temporally variable and/or over geographic areas where concentrations are less variable. By using multiple sites located in different settings, the relationships determined for estimation error versus number of measurement periods used to determine long-term average are expected to realistically portray the true distribution. Thus, the results should be a good indication of the potential errors one could expect in a variety of different cities, particularly in more northern latitudes.     

Using spatial smoothing to model a functional regression estimator to points on a lattice with application to surface-level ozone in the Eastern United States

Environmental and Ecological Statistics - Spatial functional regression methods allow researchers to model spatially dependent functional random variables, often using a kriging-based interpolation...