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

机译:尾矿池塘和矿面与逆分散模拟的量化GHG逃逸释放

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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:逆分散建模(IDM)已被成功用作助焊剂室测量的替代方法,以估计自2015年以来的监管报告的地平线油砂设施的逃逸温室气体(GHG)排放。IDM-Calpuff方法结合了Ambient GHG在每个地区源周围监测超高拉动温室气体分析仪(显着降低噪音,提高准确率);用2D和3D声波风压测量器的气象监测;用WRF,CALMET和CALPUFF模拟气象和分散模型;和贝叶斯统计反演技术。通过依靠净浓度,与尾矿池塘和矿井的所有部分相关的净浓度,在几天内,该方法在空间和时间代表性的温室气体调查中提供。 IDM-CALPUFF方法可以通过尾矿池和矿井的复杂地形,包括通过较小的占地面积或更短的范围方法检测到无法使用的区域,包括无法使用的区域进行详细和准确的空间击穿。通过遥感调查来区分。通过这样做,该方法已经了解了有针对性的缓解策略,随后证实了他们的有效性。 IDM-CALPUFF的甲烷排放估计非常稳健,测量期仅有5%的不确定性,显示多年来一致的有源矿区通量强度,并检测到意外的热点。与甲烷助熔剂和移动排放相比,矿山二氧化碳逃逸排放已被证明可忽略不计,而尾矿池有时被识别为CO_2的水槽。由于气象和操作变化,对于全年的排放,至少在季节性和理想情况下,对于最准确的年度温室气体报告和有针对性的缓解来评估季节性和理想情况下的排放。 IDM-Calpuff提供该机会。 2018 - 2019年,现场运动超出了单一监管夏季采样期,即季节性竞选期,与艾伯塔省(时代)甲烷挑战研究在地平线上进行研究。 2018年,尾矿池塘后不久,春季发生了测量运动。冬天,夏天和秋季运动正在2019年进行。

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