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Quantification of GHG Fugitive Emissions from Tailings Ponds and Mine Faces with Inverse Dispersion Modeling

机译:反向扩散模型量化尾矿池和矿井面的温室气体逸散排放

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Inverse Dispersion Modeling (IDM) has been successfully used as an alternative method to flux chamber measurements to estimate fugitive greenhouse gas (GHG) emissions from area sources at the Horizon Oil Sands facility for regulatory reporting since 2015. The IDM-CALPUFF approach combines ambient GHG monitoring with Ultraportable GHG analyzers (which significantly reduce noise and improve accuracy compared to open-path lasers) around each of the area sources; meteorological monitoring with 2D and 3D sonic anemometers; meteorological and dispersion modeling with WRF, CALMET, and CALPUFF; and a Bayesian statistical inversion technique. By relying on net concentrations, linked to emissions from all parts of the tailings pond and mine, over several days, the method delivers a spatially and temporally representative survey of GHG sources. The IDM-CALPUFF approach enables a detailed and accurate spatial breakdown of GHG fugitive emissions over the tailings pond and the complex terrain of the mine, including areas that cannot safely be sampled by in situ measurements, detected by smaller footprint or shorter range methods, or differentiated by remote sensing surveys. By doing so, the approach has informed targeted mitigation strategies and subsequently confirmed their effectiveness. Methane emission estimates with IDM-CALPUFF are very robust, with only 5% uncertainty for the measurement period, showed active mine zone flux intensities consistent over the years, and detected unexpected hot spots. Carbon dioxide fugitive emissions from the mine have been shown to be negligible, compared to methane fluxes and mobile emissions, while the tailings pond was identified as a sink of CO_2 at times. Owing to meteorological and operational variations, it is imperative to assess emissions throughout the year, at least on a seasonal and ideally on a continuous basis, for the most accurate annual GHG reporting and targeted mitigation. The IDM-CALPUFF offers that opportunity. In 2018-2019, the field campaigns were extended beyond the single regulatory summer sampling period to seasonal campaigns, in conjunction with the three-year Emission Reduction Alberta (ERA) Methane Challenge study ongoing at Horizon. In 2018, the measurement campaign occurred in the spring, shortly after the tailings pond thawed. Winter, summer, and fall campaigns are taking place in 2019.
机译:自2015年以来,反向扩散模型(IDM)已成功用作通量室测量的一种替代方法,以估算Horizo​​n油砂工厂的区域来源的短时温室气体(GHG)排放,以进行监管报告。IDM-CALPUFF方法结合了环境温室气体在每个区域源周围使用超便携式GHG分析仪(与开路激光器相比,可显着降低噪声并提高准确性)进行监视;使用2D和3D声波风速计进行气象监测;使用WRF,CALMET和CALPUFF进行气象和色散建模;和贝叶斯统计反演技术。通过依靠与尾矿池和矿山所有部分的排放相关的净浓度,在几天内,该方法可以对温室气体源进行时空代表性的调查。 IDM-CALPUFF方法可对尾矿池和矿山复杂的地形(包括无法通过现场测量安全地采样,通过较小的足迹或较短距离的方法检测到的区域)或GHG逃逸排放进行详细而准确的空间分解通过遥感调查来区分。通过这样做,该方法已为目标缓解策略提供了依据,并随后确认了其有效性。使用IDM-CALPUFF进行的甲烷排放估算非常可靠,测量期间的不确定性仅为5%,显示出多年来稳定的有效矿区通量强度,并发现了意外的热点。与甲烷通量和移动排放相比,该矿山产生的二氧化碳逃逸排放已被忽略不计,而尾矿池有时被确定为CO_2汇。由于气象和操作上的变化,必须对全年的排放量进行评估,至少要在季节性上,最好是连续地进行,以实现最准确的年度温室气体报告和有针对性的减排。 IDM-CALPUFF提供了这个机会。在2018-2019年,结合Horizo​​n正在进行的为期三年的阿尔伯塔省减排甲烷(ERA)甲烷挑战研究,该野外活动已从单个夏季监管采样期扩展到了季节性活动。 2018年,尾矿池解冻后不久,春季进行了测量活动。 2019年将开展冬季,夏季和秋季运动。

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