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Abstract. The Bakken formation contains billions of barrels of oil and gas trapped in rock and shale. Horizontal drilling and hydraulic fracturing methods have allowed for extraction of these resources, leading to exponential growth of oil production in the region over the past decade. Along with this development has come an increase in associated emissions to the atmosphere. Concern about potential impacts of these emissions on federal lands in the region prompted the National Park Service to sponsor the Bakken Air Quality Study over two winters in 2013–2014. Here we provide an overview of the study and present some initial results aimed at better understanding the impact of local oil and gas emissions on regional air quality. Data from the study, along with long-term monitoring data, suggest that while power plants are still an important emissions source in the region, emissions from oil and gas activities are impacting ambient concentrations of nitrogen oxides and black carbon and may dominate recent observed trends in pollutant concentrations at some of the study sites. Measurements of volatile organic compounds also definitively show that oil and gas emissions were present in almost every air mass sampled over a period of more than 4 months.

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We study the problem of sensor scheduling for multisensor multitarget tracking-to determine which sensors to activate over time to trade off tracking error with sensor usage costs. Formulating this problem as a Partially Observable Markov Decision Process (POMDP) gives rise to a non-myopic sensor-scheduling scheme. Our method combines sequential multisensor Joint Probabilistic Data Association (MS-JPDA) and particle filtering for belief-state estimation, and uses simulationbased Q-value approximation method for "lookahead." The example of focus in this paper involves the activation of multiple sensors simultaneously for tracking multiple targets, illustrating the effectiveness of our approach.