Source receptor analysis

Source-receptor analysis was performed to allocate the air chemistry parameters to the individual emission sources. To estimate the impact of a source group on a certain pollutant, several simulations have to be accomplished. To minimize the associated uncertainties (non-linearity of chemical processes), the source group was suppressed. Due to the non-linear chemical processes, background concentrations and advection a non-linear fraction has to be introduced (DG-ENV 2001). The source-receptor analysis is an important tool for abatement and emission reduction strategies. 

A problem In the analysis of these data Is the potential masking of some sources of variability by other correlated variables which may be difficult to quantify. For example, the potential meteorological Influences of atmospheric dispersion and mixing, scavenging differences between warm and cold clouds, variable rates of oxidation of sulfur and nitrogen species, and the dilution effect of variable rain volume may mask source-receptor chemical relationships. A particular problem Is that meteorological data and source-receptor locations share directional dependence. 

Cohen MA, Ryan PB, Spengler JD. 1991. Source-receptor study of volatile organic compounds and particulate matter in the Kanawha Valley, WV-II. Analysis of factors Contributing to VOC and particle exposure. Atmos Environ 25B 95- 107. 

Among the multivariate statistical techniques that have been used as source-receptor models, factor analysis is the most widely employed. The basic objective of factor analysis is to allow the variation within a set of data to determine the number of independent causalities, i.e. sources of particles. It also permits the combination of the measured variables into new axes for the system that can be related to specific particle sources. The principles of factor analysis are reviewed and the principal components method is illustrated by the reanalysis of aerosol composition results from Charleston, West Virginia. An alternative approach to factor analysis. Target Transformation Factor Analysis, is introduced and its application to a subset of particle composition data from the Regional Air Pollution Study (RAPS) of St. Louis, Missouri is presented. 

In this study we have employed the simultaneous collection of atmospheric particles and gases followed by multielement analysis as an approach for the determination of source-receptor relationships. A number of particulate tracer elements have previously been linked to sources (e.g., V to identify oil-fired power plant emissions, Na for marine aerosols, and Pb for motor vehicle contribution). Receptor methods commonly used to assess the interregional impact of such emissions include chemical mass balances (CMBs) and factor analysis (FA), the latter often including wind trajectories. With CMBs, source-strengths are determined (1) from the relative concentrations of marker elements measured at emission sources. When enough sample analyses are available, correlation calculations from FA and knowledge of source-emission compositions may identify groups of species from a common source type and identify potential marker elements. The source composition patterns are not necessary as the elemental concentrations in each sample are normalized to the mean value of the element. Recently a hybrid receptor model was proposed by Lewis and Stevens (2) in which the dispersion, deposition, and conversion characteristics of sulfur species in power-plant emissions... 

Aroniadou-Anderjaska V, Ennis M, Shipley MT. 1999a. Current-source density analysis in the rat olfactory bulb Laminar distribution of kainate/AMPA and NMDA receptor-mediated currents. J Neurophysiol 81 15-28. 

Standing of source-receptor relationships for nonreactive species in an airshed. The.se methods include the chemical mass balance (CMB) used for. source apportionment, the principal component analysis (PCA) used for source identification, and the empirical orthogonal function (EOF) method used for identification of the location and strengths of emission sources. A detailed review of all the variations of these basic methods is outside the scope of this book. For more information the reader is referred to treatments by Watson (1984), Henry et al. (1984), Cooper and Watson (1980), Watson et al. (1981), Macias and Hopke <1981), Dattner and Hopke (1982), Pace (1986), Watson et al. (1989), Gordon (1980, 1988), Stevens and Pace (1984), Hopke (1985, 1991), and Javitz et al. (1988). 

Ref. 44 by Ken akin is an excellent and detailed source of information for the quantitative analysis of dmg—receptor iateractions. 

ISCST3 - Industrial Source Complex - Short Term This model is used in more detailed studies of maximum air quality impacts (Phase 3 - Refined Modeling Analysis). The purpose is to compute short term concentration or deposition values, from multiple sources, on specified locations (i.e., receptors). To download the file, click the filename. This is the latest version of the regulatory model ISCST3 (00101) which was released by U.S. EPA on April 27, 2000. The file ISCST.ZIP is 1.60 MB (Executable, Source, Test Cases). You can also download the ISCST3 model evaluation references. 

Figure 6.21. Role of phospholipase D in receptor up-regulation. Neutrophils were incubated in the presence or absence of fMet-Leu-Phe and butanol for 15 min prior to analysis of expression of CDllb by FACS analysis. In (a), neutrophils were not stimulated and suspensions did not contain butanol. In (b), suspensions did not contain butanol, but were stimulated with fMet-Leu-Phe. The hatched lines show the receptor expression of suspensions incubated with 10, 20 and 30 mM butanol for 5 min prior to stimulation by fMet-Leu-Phe. Source Experiment of Fiona Watson.

PLS (partial least squares) multiple regression technique is used to estimate contributions of various polluting sources in ambient aerosol composition. The characteristics and performance of the PLS method are compared to those of chemical mass balance regression model (CMB) and target transformation factor analysis model (TTFA). Results on the Quail Roost Data, a synthetic data set generated as a basis to compare various receptor models, is reported. PLS proves to be especially useful when the elemental compositions of both the polluting sources and the aerosol samples are measured with noise and there is a high correlation in both blocks. 

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