GSTDTAP  > 地球科学
DOI10.5194/acp-20-1021-2020
Dimensionality-reduction techniques for complex mass spectrometric datasets: application to laboratory atmospheric organic oxidation experiments
Koss, Abigail R.1,4; Canagaratna, Manjula R.2; Zaytsev, Alexander3; Krechmer, Jordan E.2; Breitenlechner, Martin3; Nihill, Kevin J.1; Lim, Christopher Y.1; Rowe, James C.1; Roscioli, Joseph R.2; Keutsch, Frank N.3; Kroll, Jesse H.1
2020-01-27
发表期刊ATMOSPHERIC CHEMISTRY AND PHYSICS
ISSN1680-7316
EISSN1680-7324
出版年2020
卷号20期号:2页码:1021-1041
文章类型Article
语种英语
国家USA
英文摘要

Oxidation of organic compounds in the atmosphere produces an immensely complex mixture of product species, posing a challenge for both their measurement in laboratory studies and their inclusion in air quality and climate models. Mass spectrometry techniques can measure thousands of these species, giving insight into these chemical processes, but the datasets themselves are highly complex. Data reduction techniques that group compounds in a chemically and kinetically meaningful way provide a route to simplify the chemistry of these systems but have not been systematically investigated. Here we evaluate three approaches to reducing the dimensionality of oxidation systems measured in an environmental chamber: positive matrix factorization (PMF), hierarchical clustering analysis (HCA), and a parameterization to describe kinetics in terms of multi-generational chemistry (gamma kinetics parameterization, GKP). The evaluation is implemented by means of two datasets: synthetic data consisting of a three-generation oxidation system with known rate constants, generation numbers, and chemical pathways; and the measured products of OH-initiated oxidation of a substituted aromatic compound in a chamber experiment. We find that PMF accounts for changes in the average composition of all products during specific periods of time but does not sort compounds into generations or by another reproducible chemical process. HCA, on the other hand, can identify major groups of ions and patterns of behavior and maintains bulk chemical properties like carbon oxidation state that can be useful for modeling. The continuum of kinetic behavior observed in a typical chamber experiment can be parameterized by fitting species' time traces to the GKP, which approximates the chemistry as a linear, first-order kinetic system. The fitted parameters for each species are the number of reaction steps with OH needed to produce the species (the generation) and an effective kinetic rate constant that describes the formation and loss rates of the species. The thousands of species detected in a typical laboratory chamber experiment can be organized into a much smaller number (10-30) of groups, each of which has a characteristic chemical composition and kinetic behavior. This quantitative relationship between chemical and kinetic characteristics, and the significant reduction in the complexity of the system, provides an approach to understanding broad patterns of behavior in oxidation systems and could be exploited for mechanism development and atmospheric chemistry modeling.


领域地球科学
收录类别SCI-E
WOS记录号WOS:000509693100003
WOS关键词VOLATILITY BASIS-SET ; POSITIVE MATRIX FACTORIZATION ; MASTER CHEMICAL MECHANISM ; MCM V3 PART ; HIGH-RESOLUTION ; AEROSOL FORMATION ; TROPOSPHERIC DEGRADATION ; SOURCE APPORTIONMENT ; CLUSTER-ANALYSIS ; AIR-QUALITY
WOS类目Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/278565
专题地球科学
作者单位1.MIT, Dept Civil & Environm Engn, 77 Massachusetts Ave, Cambridge, MA 02139 USA;
2.Aerodyne Res Inc, Billerica, MA 01821 USA;
3.Harvard Univ, Paulson Sch Engn & Appl Sci, Cambridge, MA 02138 USA;
4.Tofwerk USA, Boulder, CO 80301 USA
推荐引用方式
GB/T 7714
Koss, Abigail R.,Canagaratna, Manjula R.,Zaytsev, Alexander,et al. Dimensionality-reduction techniques for complex mass spectrometric datasets: application to laboratory atmospheric organic oxidation experiments[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2020,20(2):1021-1041.
APA Koss, Abigail R..,Canagaratna, Manjula R..,Zaytsev, Alexander.,Krechmer, Jordan E..,Breitenlechner, Martin.,...&Kroll, Jesse H..(2020).Dimensionality-reduction techniques for complex mass spectrometric datasets: application to laboratory atmospheric organic oxidation experiments.ATMOSPHERIC CHEMISTRY AND PHYSICS,20(2),1021-1041.
MLA Koss, Abigail R.,et al."Dimensionality-reduction techniques for complex mass spectrometric datasets: application to laboratory atmospheric organic oxidation experiments".ATMOSPHERIC CHEMISTRY AND PHYSICS 20.2(2020):1021-1041.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Koss, Abigail R.]的文章
[Canagaratna, Manjula R.]的文章
[Zaytsev, Alexander]的文章
百度学术
百度学术中相似的文章
[Koss, Abigail R.]的文章
[Canagaratna, Manjula R.]的文章
[Zaytsev, Alexander]的文章
必应学术
必应学术中相似的文章
[Koss, Abigail R.]的文章
[Canagaratna, Manjula R.]的文章
[Zaytsev, Alexander]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。