Estimation of gas emissions from a waste pond using micrometeorological approaches: Footprint sensitivities and complications

IF 3.8 Q2 ENVIRONMENTAL SCIENCES Atmospheric Environment: X Pub Date : 2023-08-01 DOI:10.1016/j.aeaoa.2023.100219
Thomas K. Flesch , Lowry A. Harper , Trevor W. Coates , Peter J. Carlson
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Abstract

The quantification of gas emissions from waste storage and treatment ponds is an important problem. The objective of this study was to better understand the use of micrometeorological techniques for this purpose. Methane emissions were estimated from a large tailings pond (surface area >11 km2) at an oil sands mine site using datasets collected by different groups over a nine-month period. Emissions were calculated with eddy-covariance (EC) and inverse dispersion modelling (IDM) techniques. Three different IDM calculations were made using methane concentrations measured with either fixed-point sensors (IDM-LGR), a long-path laser (IDM-GL), or an unmanned aerial vehicle (IDM-UAV). Emissions were also estimated from a flux-chamber (FC) survey. Although the temporal overlap between the different datasets was limited, the results indicate substantial differences in emission-rate estimates. During a summer interval the EC, IDM-LGR, and IDM-GL estimates were 19%, 41%, and 56% of the FC-estimated rate, respectively. The overall ordering was EC ≈ IDM-UAV < IDM-LGR < IDM-GL < FC. Differences in the emission estimates appear to be explained by the physical location of the measurement footprints. The EC and IDM-UAV footprints were comparably small and confined to lower emitting areas of the pond, while the larger IDM-LGR and IDM-GL footprints included higher emitting areas. It would seem sensible to prefer the larger footprint IDM approaches for this large pond. However, the large IDM footprints necessitated a complicated analysis to remove the influence of an adjacent methane source in the calculations. This study illustrates the importance of understanding the footprint of micrometeorological techniques when quantifying emissions and the complications that arise when the footprint does not match the source area.

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使用微气象方法估算废水池的气体排放:足迹敏感性和复杂性
废物储存池和处理池气体排放的量化是一个重要的问题。这项研究的目的是为了更好地了解微气象技术在这方面的应用。利用不同小组在9个月期间收集的数据集,估算了油砂矿场一个大型尾矿库(表面积11平方公里)的甲烷排放量。利用涡流协方差(EC)和逆色散模型(IDM)技术计算辐射。使用定点传感器(IDM- lgr)、长程激光(IDM- gl)或无人机(IDM- uav)测量甲烷浓度,进行了三种不同的IDM计算。还通过通量室(FC)调查估计了排放量。虽然不同数据集之间的时间重叠是有限的,但结果表明在排放率估计上存在实质性差异。在夏季,EC、IDM-LGR和IDM-GL的估计值分别为fc估计值的19%、41%和56%。总体排序为EC≈IDM-UAV <IDM-LGR & lt;IDM-GL & lt;FC。排放估计值的差异似乎可以用测量足迹的物理位置来解释。EC和IDM-UAV足迹相对较小,局限于池塘的低发射区,而较大的IDM-LGR和IDM-GL足迹包括高发射区。对于这个大池塘,更倾向于使用占用空间更大的IDM方法似乎是明智的。然而,大量的IDM足迹需要进行复杂的分析,以消除计算中相邻甲烷源的影响。这项研究说明了在量化排放时理解微气象技术的足迹的重要性,以及当足迹与源区域不匹配时出现的复杂性。
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来源期刊
Atmospheric Environment: X
Atmospheric Environment: X Environmental Science-Environmental Science (all)
CiteScore
8.00
自引率
0.00%
发文量
47
审稿时长
12 weeks
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