Alternate approaches for assessing impacts of oil sands development on air quality: A case study using the First Nation Community of Fort McKay

Previous analyses of continuously measured compounds in Fort McKay, an indigenous community in the Athabasca Oil Sands, have detected increasing concentrations of nitrogen dioxide (NO₂) and total hydrocarbons (THC), but not of sulfur dioxide (SO₂), ozone (O₃), total reduced sulfur compounds (TRS), or particulate matter (aerodynamic diameter <2.5 μm; PM_2.5). Yet the community frequently experiences odors, dust, and reduced air quality. The authors used Fort McKay’s continuously monitored air quality data (1998–2014) as a case study to assess techniques for air quality analysis that make no assumptions regarding type of change. Linear trend analysis detected increasing concentrations of higher percentiles of NO₂, nitric oxide (NO), and nitrogen oxides (NO_x), and THC. However, comparisons of all compounds between an early industrial expansion period (1998–2001) and current day (2011–2014) show that concentrations of NO₂, SO₂, THC, TRS, and PM_2.5 have significantly increased, whereas concentrations of O₃ are significantly lower. An assessment of the frequency and duration of periods when concentrations of each compound were above a variety of thresholds indicated that the frequency of air quality events is increasing for NO₂ and THC. Assessment of change over time with odds ratios of the 25th, 50th, 75th, and 90th percentile concentrations for each compound compared with an estimate of natural background variability showed that concentrations of TRS, SO₂, and THC are dynamic, higher than background, and changes are nonlinear and nonmonotonic. An assessment of concentrations as a function of wind direction showed a clear and generally increasing influence of industry on air quality. This work shows that evaluating air quality without assumptions of linearity reveals dynamic changes in air quality in Fort McKay, and that it is increasingly being affected by oil sands operations.

Implications: Understanding the nature and types of air quality changes occurring in a community or region is essential for the development of appropriate air quality management policies. Time-series trending of air quality data is a common tool for assessing air quality changes and is often used to assess the effectiveness of current emission management programs. The use of this tool, in the context of oil sands development, has significant limitations, and alternate air quality change analysis approaches need to be applied to ensure that the impact of this development on air quality is fully understood so that appropriate emission management actions can be taken.