Quantification of fugitive emissions from an oil sands tailings pond by eddy covariance

Zhang, Lucas; Cho, Sunny; Hashisho, Zaher; Brown, Casandra

doi:10.1016/j.fuel.2018.09.104

Cited by 15 publications

(15 citation statements)

References 30 publications

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“…S4 (d)) covered a workers' lodge and parking lots, and CH4 emissions and diurnal variation were close to zero. The lack 250 of a diurnal variation of CH4 EC flux observed when the wind was from the pond in this study was similar to the diurnal variation of CH4 EC flux at another tailings pond reported by Zhang et al (2019).…”

Section: Eddy Covariance Fluxsupporting

confidence: 89%

“…Results from this study and Zhang et al (2019) suggest that average tailings pond CH4 emission extrapolated from a few individual flux chamber measurements may significantly underestimate or overestimate fluxes relative to area-320 averaging micrometeorological measurements.…”

Section: Flux Chamber Measurementsmentioning

confidence: 79%

“…There have been a number of studies to quantify the emissions of pollutants to the atmosphere from the various industrial activities associated with the Oil Sands (Simpson et al, 2010;Liggio et al, 2016;Baray et al, 2018;Liggio et al, 2019). Pollutant emissions that have been observed from tailings ponds include greenhouse gases (GHGs, mainly methane (CH4) and carbon dioxide (CO2)), reduced sulphur compounds, 30 volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs) (Siddique et al, 2007;Simpson et al, 2010;Yeh et al, 2010;Siddique et al, 2011;Siddique et al, 2012;Galarneau et al 2014;Small et al, 2015; Bari and Kindzierski, 2018;Zhang et al,2019). However, published studies on atmospheric emissions from tailings https://doi.org/10.5194/amt-2020-116 Preprint.…”

Section: Introduction 20mentioning

confidence: 99%

“…ponds have been rare (Galarneau et al, 2014;Small et al 2015;Zhang et al 2019), and significant gaps remain regarding their contribution to total emission from oil sands operations (Small et al, 2015). 35…”

Section: Introduction 20mentioning

confidence: 99%

See 3 more Smart Citations

Methane emissions from an oil sands tailings pond: A quantitative comparison of fluxes derived by different methods

You¹,

Staebler²,

Moussa³

et al. 2020

Preprint

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Abstract. Tailings ponds in the Alberta Oil Sands Region are significant sources of fugitive emissions of methane to the atmosphere, but detailed knowledge on spatial and temporal variabilities is lacking due to limitations of the methods deployed under current regulatory compliance monitoring programs. To develop more robust and representative methods for quantifying these emissions, three micrometeorological flux methods were applied along with traditional flux chambers to determine fluxes over a 5-week period. Eddy covariance flux measurements provided the benchmark. A method is presented to directly calculate stability-corrected eddy diffusivities that can be applied to vertical gas profiles for gradient flux estimation. Gradient fluxes were shown to agree with eddy covariance within 7 %, and inverse dispersion model fluxes within 11 %, with an overall uncertainty of 28 % for the calculated mean flux. Fluxes were shown to have only a minor diurnal cycle (18 % variability) and to be mostly independent of wind speed, air and water surface temperatures. Flux chambers underestimated the fluxes by a factor of 2 in this particular campaign. These measurements indicate that the larger footprint of micrometeorological measurements results in more robust emission estimates representing the whole pond.

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Section: Eddy Covariance Fluxsupporting

confidence: 89%

Section: Flux Chamber Measurementsmentioning

confidence: 79%

Section: Introduction 20mentioning

confidence: 99%

Section: Introduction 20mentioning

confidence: 99%

See 2 more Smart Citations

Methane emissions from an oil sands tailings pond: A quantitative comparison of fluxes derived by different methods

You¹,

Staebler²,

Moussa³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…For CO 2 emission flux, the average was 4.32 µmol/(m 2sec) and 3.22 µmol/(m 2 -sec) for day 1 and day 2, respectively ( Figures 9 and 10 and Table 1). These emissions fluxes are of the same order of magnitude as determined using eddy covariance technique at a similar lagoon (30min average data over 3 months in summer 2013) (Zhang et al, 2014). It is apparent that stronger wind speed on day 1 corresponds to higher emission fluxes of CH 4 and CO 2 from the lagoon as compared to day 2.…”

Section: Resultssupporting

confidence: 64%

Autonomous mobile platform for monitoring air emissions from industrial and municipal wastewater ponds

Huda

Yang

et al. 2017

Journal of the Air & Waste Management Association

Self Cite

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The Mobile Platform demonstrated in this study has the ability to measure greenhouse gas (GHG) emissions from fugitive sources such as municipal wastewater lagoons. This technology can be used to measure emission fluxes from tailings ponds with better detection of spatial and temporal variations of fugitive emissions. Additional air and water sampling equipment could be added to the mobile platform for a broad range of air and water quality studies in the oil sands region of Alberta.

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A decadal synthesis of atmospheric emissions, ambient air quality, and deposition in the oil sands region

Horb

Wentworth

Makar

et al. 2021

Integr Envir Assess & Manag

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This review is part of a series synthesizing peer‐reviewed literature from the past decade on environmental monitoring in the oil sands region (OSR) of northeastern Alberta. It focuses on atmospheric emissions, air quality, and deposition in and downwind of the OSR. Most published monitoring and research activities were concentrated in the surface‐mineable region in the Athabasca OSR. Substantial progress has been made in understanding oil sands (OS)‐related emission sources using multiple approaches: airborne measurements, satellite measurements, source emission testing, deterministic modeling, and source apportionment modeling. These approaches generally yield consistent results, indicating OS‐related sources are regional contributors to nearly all air pollutants. Most pollutants exhibit enhanced air concentrations within ~20 km of surface‐mining activities, with some enhanced >100 km downwind. Some pollutants (e.g., sulfur dioxide, nitrogen oxides) undergo transformations as they are transported through the atmosphere. Deposition rates of OS‐related substances primarily emitted as fugitive dust are enhanced within ~30 km of surface‐mining activities, whereas gaseous and fine particulate emissions have a more diffuse deposition enhancement pattern extending hundreds of kilometers downwind. In general, air quality guidelines are not exceeded, although these single‐pollutant thresholds are not comprehensive indicators of air quality. Odor events have occurred in communities near OS industrial activities, although it can be difficult to attribute events to specific pollutants or sources. Nitrogen, sulfur, polycyclic aromatic compounds (PACs), and base cations from OS sources occur in the environment, but explicit and deleterious responses of organisms to these pollutants are not as apparent across all study environments; details of biological monitoring are discussed further in other papers in this special series. However, modeling of critical load exceedances suggests that, at continued emission levels, ecological change may occur in future. Knowledge gaps and recommendations for future work to address these gaps are also presented. Integr Environ Assess Manag 2022;18:333–360. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

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Quantification of fugitive emissions from an oil sands tailings pond by eddy covariance

Cited by 15 publications

References 30 publications

Methane emissions from an oil sands tailings pond: A quantitative comparison of fluxes derived by different methods

Methane emissions from an oil sands tailings pond: A quantitative comparison of fluxes derived by different methods

Autonomous mobile platform for monitoring air emissions from industrial and municipal wastewater ponds

A decadal synthesis of atmospheric emissions, ambient air quality, and deposition in the oil sands region

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