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Satellite-derived methane hotspot emission estimates using a fast data-driven method

机译:使用快速数据驱动方法卫星衍生的甲烷热点发射估计

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Methane is an important atmospheric greenhouse gas and an adequate understanding of its emission sources is needed for climate change assessments, predictions, and the development and verification of emission mitigation strategies. Satellite retrievals of near-surface-sensitive column-averaged dry-air mole fractions of atmospheric methane, i.e. XCH4, can be used to quantify methane emissions. Maps of time-averaged satellite-derived XCH4 show regionally elevated methane over several methane source regions. In order to obtain methane emissions of these source regions we use a simple and fast data-driven method to estimate annual methane emissions and corresponding 1σ uncertainties directly from maps of annually averaged satellite XCH4. From theoretical considerations we expect that our method tends to underestimate emissions. When applying our method to high-resolution atmospheric methane simulations, we typically find agreement within the uncertainty range of our method (often 100?%) but also find that our method tends to underestimate emissions by typically about 40?%. To what extent these findings are model dependent needs to be assessed. We apply our method to an ensemble of satellite XCH4 data products consisting of two products from SCIAMACHY/ENVISAT and two products from TANSO-FTS/GOSAT covering the time period 2003–2014. We obtain annual emissions of four source areas: Four Corners in the south-western USA, the southern part of Central Valley, California, Azerbaijan, and Turkmenistan. We find that our estimated emissions are in good agreement with independently derived estimates for Four Corners and Azerbaijan. For the Central Valley and Turkmenistan our estimated annual emissions are higher compared to the EDGAR v4.2 anthropogenic emission inventory. For Turkmenistan we find on average about 50?% higher emissions with our annual emission uncertainty estimates overlapping with the EDGAR emissions. For the region around Bakersfield in the Central Valley we find a factor of 5–8 higher emissions compared to EDGAR, albeit with large uncertainty. Major methane emission sources in this region are oil/gas and livestock. Our findings corroborate recently published studies based on aircraft and satellite measurements and new bottom-up estimates reporting significantly underestimated methane emissions of oil/gas and/or livestock in this area in EDGAR.
机译:气候变化评估,预测和减排策略的开发和验证,需要对其排放来源充分了解其排放来源的重要大气温室气体。近表面敏感柱平均干气摩尔分数的卫星检索,即Xch4,可用于量化甲烷排放。时间平均卫星衍生的XCH4的映射在几个甲烷源区上显示出区升高的甲烷。为了获得这些源区的甲烷排放,我们使用简单快速的数据驱动方法来估计每年甲烷排放和相应的1σ不确定性直接来自每年平均卫星XCH4的地图。从理论考虑来看,我们预计我们的方法往往低估排放。在将方法应用于高分辨率大气甲烷模拟时,我们通常在我们的方法的不确定性范围内找到一致性(通常100?%),但也发现我们的方法往往会低估排放量为约40℃。需要评估这些发现的模式的模型依赖性。我们将我们的方法应用于卫星XCH4数据产品的集合,由Sciamachy / Envisat的两种产品和来自Tanso-FTS / GOSAT的两种产品组成,涵盖2003-2014的时间段。我们获得了四个来源区的年排放量:美国西南部四个角落,中央山谷南部,加州,阿塞拜疆和土库曼斯坦。我们发现,我们的估计排放与四个角落和阿塞拜疆的独立衍生估计吻合良好。对于中央山谷和土库曼斯坦,与Edgar V4.2人为排放库存相比,我们估计的年度排放量更高。对于土库曼斯坦,我们发现平均约为50?%的较高排放量,我们的年度排放不确定性估计与Edgar排放重叠。对于中央山谷周围的地区,与Edgar相比,我们发现了5-8个更高的排放量,尽管具有大的不确定性。该地区主要甲烷排放源是油/煤气和牲畜。我们的研究结果证实了基于飞机和卫星测量的最近发表的研究以及新的自下而上的估计,报告在埃德加这个地区的石油/天然气和/或牲畜的甲烷排放显着低估了。
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