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Organic aerosol source apportionment in London 2013 with ME-2: exploring the solution space with annual and seasonal analysis

机译:使用ME-2在2013年伦敦举行的有机气溶胶源分配:通过年度和季节分析探索解决方案空间

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The multilinear engine (ME-2) factorization tool is being widely used following the recent development of the Source Finder (SoFi) interface at the Paul Scherrer Institute. However, the success of this tool, when using the a value approach, largely depends on the inputs (i.e. target profiles) applied as well as the experience of the user. A strategy to explore the solution space is proposed, in which the solution that best describes the organic aerosol (OA) sources is determined according to the systematic application of predefined statistical tests. This includes trilinear regression, which proves to be a useful tool for comparing different ME-2 solutions. Aerosol Chemical Speciation Monitor (ACSM) measurements were carried out at the urban background site of North Kensington, London from March to December 2013, where for the first time the behaviour of OA sources and their possible environmental implications were studied using an ACSM. Five OA sources were identified: biomass burning OA (BBOA), hydrocarbon-like OA (HOA), cooking OA (COA), semivolatile oxygenated OA (SVOOA) and low-volatility oxygenated OA (LVOOA). ME-2 analysis of the seasonal data sets (spring, summer and autumn) showed a higher variability in the OA sources that was not detected in the combined March-December data set; this variability was explored with the triangle plots f 44 : f 43 f 44 : f 60, in which a high variation of SVOOA relative to LVOOA was observed in the f 44 : f 43 analysis. Hence, it was possible to conclude that, when performing source apportionment to long-term measurements, important information may be lost and this analysis should be done to short periods of time, such as seasonally. Further analysis on the atmospheric implications of these OA sources was carried out, identifying evidence of the possible contribution of heavyduty diesel vehicles to air pollution during weekdays compared to those fuelled by petrol.
机译:随着Paul Scherrer研究所对Source Finder(SoFi)接口的最新开发,多线性引擎(ME-2)分解工具被广泛使用。但是,使用价值方法时,此工具的成功很大程度上取决于所应用的输入(即目标配置文件)以及用户的体验。提出了一种探索解决方案空间的策略,其中根据预定义的统计测试的系统应用来确定最能描述有机气溶胶(OA)来源的解决方案。这包括三线性回归,这被证明是比较不同ME-2解决方案的有用工具。 2013年3月至12月,在伦敦北肯辛顿的市区背景进行了气溶胶化学形态监测器(ACSM)的测量,首次使用ACSM研究了OA来源的行为及其可能的环境影响。确定了五个OA来源:生物质燃烧OA(BBOA),类烃OA(HOA),蒸煮OA(COA),半挥发性氧化OA(SVOOA)和低挥发性氧化OA(LVOOA)。 ME-2对季节性数据集(春季,夏季和秋季)的分析显示,OA来源中的变异性较高,在3月至12月的合并数据集中未检测到。通过三角图f 44:f 43 f 44:f 60探索了这种可变性,其中在f 44:f 43分析中观察到SVOOA相对于LVOOA的高变化。因此,有可能得出这样的结论:在对长期测量进行源分配时,可能会丢失重要信息,并且应在短时期内(例如季节性)进行此分析。对这些OA源对大气的影响进行了进一步分析,确定了证据表明重型柴油车与汽油相比可能在工作日造成空气污染。

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