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PM source apportionment and health effects: 1. Intercomparison of source apportionment results.

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TLDR
Overall, although these intercomparisons suggest areas where further research is needed, they provide support the contention that PM2.5 mass source apportionment results are consistent across users and methods, and that today's sourceapportionment methods are robust enough for application to PM2-5 health effects assessments.
Abstract
During the past three decades, receptor models have been used to identify and apportion ambient concentrations to sources. A number of groups are employing these methods to provide input into air quality management planning. A workshop has explored the use of resolved source contributions in health effects models. Multiple groups have analyzed particulate composition data sets from Washington, DC and Phoenix, AZ. Similar source profiles were extracted from these data sets by the investigators using different factor analysis methods. There was good agreement among the major resolved source types. Crustal (soil), sulfate, oil, and salt were the sources that were most unambiguously identified (generally highest correlation across the sites). Traffic and vegetative burning showed considerable variability among the results with variability in the ability of the methods to partition the motor vehicle contributions between gasoline and diesel vehicles. However, if the total motor vehicle contributions are estimated, good correspondence was obtained among the results. The source impacts were especially similar across various analyses for the larger mass contributors (e.g., in Washington, secondary sulfate SE=7% and 11% for traffic; in Phoenix, secondary sulfate SE=17% and 7% for traffic). Especially important for time-series health effects assessment, the source-specific impacts were found to be highly correlated across analysis methods/researchers for the major components (e.g., mean analysis to analysis correlation, r>0.9 for traffic and secondary sulfates in Phoenix and for traffic and secondary nitrates in Washington. The sulfate mean r value is >0.75 in Washington.). Overall, although these intercomparisons suggest areas where further research is needed (e.g., better division of traffic emissions between diesel and gasoline vehicles), they provide support the contention that PM2.5 mass source apportionment results are consistent across users and methods, and that today's source apportionment methods are robust enough for application to PM2.5 health effects assessments.

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Journal ArticleDOI

Spatial and Temporal Variation in PM2.5 Chemical Composition in the United States for Health Effects Studies

TL;DR: This work characterizes spatial and temporal variability of PM2.5 components in the United States to determine whether their daily variation is associated with daily variation of health indicators, and whether their seasonal and regional patterns can explain the seasonal and Regional heterogeneity in PM10 (PM with aerodynamic diameter < 10 μm) and PM1.5 health risks.
Journal ArticleDOI

Health Effects of Organic Aerosols

TL;DR: A review focusing on hazard identification and exposure assessment for evaluating risks to public health from ambient organic aerosols is presented in this article, which identifies key information gaps and presents a conceptual framework for research priorities for resolving those gaps.
Journal ArticleDOI

Protecting human health from air pollution: shifting from a single-pollutant to a multipollutant approach.

TL;DR: To date, the assessment of public health consequences of air pollution has largely focused on a single-pollutant approach aimed at estimating the increased risk of adverse health outcomes associated with the Exposure to a single air pollutant, adjusted for the exposure to other air pollutants.
References
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Book

Solving least squares problems

TL;DR: Since the lm function provides a lot of features it is rather complicated so it is going to instead use the function lsfit as a model, which computes only the coefficient estimates and the residuals.
Book

Modern factor analysis

TL;DR: The third edition of HARMAN's authoritative text as mentioned in this paper incorporates the many new advances made in computer science and technology over the last ten years The author gives full coverage to both theoretical and applied aspects of factor analysis from its foundations through the most advanced techniques This highly readable text will be welcomed by researchers and students working in psychology, statistics, economics and related disciplines
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Modern Factor Analysis

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Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values†

TL;DR: In this paper, a new variant of Factor Analysis (PMF) is described, where the problem is solved in the weighted least squares sense: G and F are determined so that the Frobenius norm of E divided (element-by-element) by σ is minimized.
Book

Factor Analysis in Chemistry

TL;DR: This book discusses Mathematical Formulation of Target Factor Analysis and its Applications, including Nuclear Magnetic Resonance, Chromatography, and Multimode Factor Analysis.
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