Source Apportionment of Atmospheric Trace Gases and Particulate Matter: Comparison of Log-ratio and Traditional Approaches
dc.contributor.author
dc.date.accessioned
2017-02-17T08:00:23Z
dc.date.available
2017-02-17T08:00:23Z
dc.date.issued
2011-05-11
dc.identifier.isbn
978-84-87867-76-7
dc.identifier.uri
dc.description.abstract
In this paper we compare multivariate methods using both traditional approaches, which
ignore issues of closure and provide relatively simple methods to deal with censored or
missing data, and log-ratio methods to determine the sources of trace constituents in the
atmosphere. The data set examined was collected from April to July 2008 at a sampling site
near Woods Hole, Massachusetts, along the northeastern United States Atlantic coastline.
The data set consists of trace gas mixing ratios (O3, SO2, NOx, elemental mercury [Hgo
], and
reactive gaseous mercury [RGM]), and concentrations of trace elements in fine (<2.5 µm)
particulate matter (Al, As, Ba, Ca, Cd, Ce, Co, Cs, Fe, Ga, Hg, K, La, Mg, Mn, Na, P, Pb,
Rb, Sb, Sr, Th, Ti, V, Y, and Zn) with varying percentages of censored values for each
species.
The data were separated into two subcompositions: s1, which is comprised by RGM and
particulate Hg (HgP), which are both highly censored; and s2 which includes all of the trace
elements associated with particulate matter except Hg, and the trace gases O3, SO2, NOx, and
Hgo
. Principal factor analysis (PFA) was successful in determining the primary sources for
constituents in s2 using both traditional and log-ratio approaches. Using the traditional
approach, regression between factor scores and RGM and particulate Hg concentrations
suggested that none of the sources identified during PFA led to positive contributions of
either reactive mercury compound. This finding is counter to most conventional thinking and
is likely specious, resulting from removal of censored data (up to >80% of the entire dataset)
during the analysis.
Log-ratio approaches to find relationships between constituents comprising s2 with RGM
and HgP (i.e., s1) focused on log-ratio correlation and regression analyses of alr-transformed
data, using Al as the divisor. Regression models accounted for large fractions of the variance
in concentrations of the two reactive mercury species and generally agreed with
conceptualizations about the formation and behavior of these species. An analysis of
independence between the subcompositions demonstrated that the behavior of the two
constituents comprising s1 (i.e., RGM and HgP) is dependent on changes in s2. Our findings
suggest that although problems related to closure are largely unknown or ignored in the
atmospheric sciences, much insight can be gleaned from the application of log-ratio methods
to atmospheric chemistry data
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
Universitat Politècnica de Catalunya. Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE)
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Reproducció digital del document publicat a:
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© International Workshop on Compositional Data Analysis (4th: 2011: Sant Feliu de GuÍxols, Girona). CODAWORK 2011: International Workshop on Compositional Data Analysis, hold on May 9-13rd. 2011, Sant Feliu de Guíxols, Girona
dc.relation.ispartofseries
Llibres / Capítols de LLibre (D-IMAE)
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Tots els drets reservats
dc.subject
dc.title
Source Apportionment of Atmospheric Trace Gases and Particulate Matter: Comparison of Log-ratio and Traditional Approaches
dc.type
info:eu-repo/semantics/bookPart
dc.rights.accessRights
info:eu-repo/semantics/openAccess