Chemical Mass Balance CMB

If the source fingerprints, for each of n sources are known and the number of sources is less than or equal to the number of measured species (n < m), an estimate for the solution to the system of equations (3) can be obtained. If m > n, then the set of equations is overdetermined, and least-squares or linear programming techniques are used to solve for L. This is the basis of the chemical mass balance (CMB) method (20,21). If each source emits a particular species unique to it, then a very simple tracer technique can be used (5). Examples of commonly used tracers are lead and bromine from mobile sources, nickel from fuel oil, and sodium from sea salt. The condition that each source have a unique tracer species is not often met in practice. 

The two most widespread statistical receptor models in the literature are regression model of chemical mass balance (CMB) and target transformation factor analysis (TTFA) (. ) The questions to be answered by the receptor models are ... 

The development of new source apportionment methods have, for the first time, led to the development of regional particulate control strategies. Source impacts assigned using a chemical mass balance (CMB) model have been used in association with airshed dispersion models to identify emission inventory deficiencies and Improve modeling assumptions. 

Receptor models are widely used tools for apportioning concentrations of pollutants to different sources. They can be factor analytical methods (PMF, PCA, UNMIX, etc.) or chemical mass balance (CMB). On the one hand, these methods revealed to be very valuable to identify the main sources/categories of PM pollution (road traffic, secondary particles, fuel oil combustion, sea salt, etc.) but on the other hand they experienced difficulties in separating the contributions of collinear sources such as mineral dust (natural resuspension) and road dust (anthropogenic) or co-variant sources such as vehicle exhaust and road dust [34, 44, 45, 49, 55, 58, 110-113]). Significant improvements were made with the use of combination of models or constrained models such as the Multilinear Engine (ME-2). 

Accurate knowledge of compositions of particles released by pollution sources is required by receptor modelers, e.g., for Chemical Mass Balances (CMBs). To improve model calculations, we have developed a source-composition library of data from journals, reports, and unpublished work. The library makes the data readily available and also helps to identify what new data are most needed. The library includes data for 21 studies of coal-fired plants. These data were used to investigate effects of coal type, pollution control device, and particle size on plant emissions. 

Trace element compositions of airborne particles are important for determining sources and behavior of regional aerosol, as emissions from major sources are characterized by their elemental composition patterns. We have investigated airborne trace elements in a complex regional environment through application of receptor models. A subset (200) of fine fraction samples collected by Shaw and Paur (1,2) in the Ohio River Valley (ORV) and analyzed by x-ray fluorescence (XRF) were re-analyzed by instrumental neutron activation analysis (INAA). The combined data set, XRF plus INAA, was subjected to receptor-model interpretations, including chemical mass balances (CMBs) and factor analysis (FA). Back trajectories of air masses were calculated for each sampling period and used with XRF data to select samples to be analyzed by INAA. 

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... 

The chemical mass balance (CMB) method depends on the inversion of (13.11) or (13.12) to obtain the source contributions mj or Anij. Values of pi are measured at a given sampling site. The matrix Cij should also correspond to the point of measurement. Usually, however, it is assumed that the value of c,-/ is equal to (he value at the source, and fractionation by exchange with (he gas phase or by sedimentation is neglected. Hence in carrying out the chemical element balance, it is necessary to choose elements for which fractionation is not tmportanl. 

For the assessment of the contribution of the emission categories to the observed NMVOC concentrations the Chemical Mass Balance (CMB) modelling technique, version 8 from United States Environmental Protection Agency (Watson et al., 1998 Watson et al., 2001) was selected. The method uses source specific ratios between the emission rates of certain set of compounds and aims to recognise these fingerprints, or soiuce profiles, in the profile measured at the receptor point. As a result the CMB model delivers contributions from each source type to the total ambient NMVOC and individual hydrocarbon species at receptor points and their uncertainties. 

Results for elements in aerosol samples which are obtained by multielement techniques from data sets from which information about the sources of the components can be extracted (Gordon 1980). Such methods which make use of data obtained at receptor points are called receptor models. The most important receptor models are chemical mass balances (CMB), enrichment factors, time series correlation, multivariate models and spatial models (Cooper and Watson 1980 Gordon 1988). Dispersion modeling has also been used to explain the... 

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). 

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