Receptor Modeling for Air Quality Management (Data Handling in Science and Technology)


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Source apportionment of personal exposure of fine particulates among school communities in India Most Downloaded Articles

Locate samplers and windvanes at these sites and sample simultaneously with the other receptor sites. Analyze samples for all days on which the sampler is downwind of the source. Determine which components of the sample are due to the source in question. The last point is the hardest to accomplish and reverts to the question of, "If that can be done, who needs the receptor model? In-stack testing procedures are still under development with a greater inclination on the part of developers to produce samples of use for receptor modeling.

Detailed studies of large point sources should be done in such a way as to enhance the generality of the results.

The relevant operating parameters affecting emission compositions need to be identified, measured and reported with each source test. It is only with this information that the test results can be evaluated for use in receptor model studies other than that for which the test was made. Studies of motor vehicle emissions are difficult now and will become even more so as lead is phased out of gasoline. Studies of tailpipe emissions should be done with dilution and cooling of the exhaust.

A serious drawback of individual automobile testing is the variability of emissions compositon as a function of car and driving cycle. In his review of the automobile emissions literature, Watson found the lead composition of auto exhaust varying from 12 to 70 percent, depending on the test.

Global Air Quality: Management and Science MSc

Studies in tunnels Pierson and Bracheczek, , Ondov et al. At present, no components unique to diesel exhaust have been found, and with the phase-out of lead in gasoline, the major tracer for conventional engines is being lost. Much greater emphasis on the characterization of this universal aerosol source category is required.

The characterization of fugitive emissions, those originating from roadways, storage piles, and rock crushers, is extremely important for the source apportionment of the total and coarse suspended particulate matter fractions of ambient concentrations. Once likely sources are identified, ambient samples can be taken at site or bulk material can be taken to the laboratory, resuspended and sampled on a filter substrate and analyzed.

Source characterization results are not located in a centralized facility which is constantly updated, and each researcher has to assemble his own collection of results or use the assemblage of someone else which may not be applicable to the case under study. This existing computerized structure can provide the centralized location for receptor model source characterization information.

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Receptor Modeling for Air Quality Management -- Hopke, P.K. -ѕ©¶«ФД¶Б-ФЪПЯФД¶Б

Procedures such as those described for ambient data in the previous section, need to be developed which will allow receptor model users to access this data base over telephone lines. The data required of receptor model source tests should be incorporated into the EADS and source characterization results should report this information in an EADS compatible format. Future development efforts in source characterization should include: Develop new source sampling methods including tethered balloon and ground based sampling.

Standardize data reporting and management procedures and store all data in a central data base. Create a chemical component analysis protocol to obtain maximum information from each source test. Though several methods are multi-species, able to quantify a number of chemical components simultaneously, no single method is sufficient to both quantify the majority of the collected particulate matter mass and those components which serve to identify and quantify source contributions.

These apply not only to the analytical method, but to the laboratory performing the method. The necessary criteria are: 1. The analytical method must have been developed and tested specifically for the analysis of suspended particulate matter. Lower quantifiable concentrations of the method must be less than the concentrations expected from the ambient samples taken. The method must be free of biases for all components quantified.

Lucas Gomes

The values achieved by the method must be reproducible within defined and reasonable confidence intervals. If an analytical method is successful for certain types of environmental samples, it is convenient to assume that it is appropriate for all samples. Hard and bitter experience shows this not to be the case for suspended particulate matter. Before a procedure can be accepted, one must have identified and corrected likely interferences, defined amenable aerosol collection substrates and sampling requirements, considered the effects of different aerosol matrices, and verified its ability to meet the final three criteria.

The amount of suspended particulate matter available for analysis depends on the ambient concentration, the flowrate of air through the substrate, the sampling duration, and the fraction of the sample presented for analysis. Cooper provides a useful tabulation of typical concentrations and ranges of urban aerosol elemental concentrations; it would be helpful to update this summary, expand it to certain chemical compounds, and stratify it by site types urban, rural, etc. The expected amounts available for analysis should be a factor of ten or more above the lower quantifiable concentrations of the analytical method.

Intermethod comparisons are better for evaluating accuracy since interlaboratory analyses using the same method will exhibit the same types of biases. Urban Particulate Matter Standard Reference Material Greenberg, provides a means for initial and routine verification of accuracy. The concentrations of additional chemical components in this standard need to be quantified and their constancy with time assessed. NBS 16A8 was collected in St. Louis and is representative of the eastern city aerosol matrix. Other aerosol standards from a variety of locations would be helpful for the evaluation of analytical bias.

The data from replicate analysis should be used to define the precision of each value measured. The desirable criteria are: 1. The method should measure a number of components in a single analysis. The analysis should be non-destructive. The analysis should be cost-effective. Many analysis techniques are capable of measuring more than one chemical component of interest with adequate precision, accuracy and sensitivity. Not only do these methods save the cost of many individual analyses, they minimize the amount of sample required. A non-destructive method is preferred since the sample can be made available for other analyses to verify the non-destructive results or to complement them with the measurement of additional chemical components.

Given the choice of analytical methods meeting the necessary and desirable criteria, the least expensive analysis per sample should be chosen. This choice may vary with the number of samples to be processed. A complete review of all methods applied in the past with a view toward their use for receptor modeling does not exist, and its production would be a useful contribution to the state-of-the-art.

Several analytical tools have been found to meet the stated criteria, or are in the development stages of trying to meet them, and are being used to supply the input measurements for receptor models. One means of classifying available and useful analysis procedures for source and receptor studies consists of the following categories: 1. Elements with atomic number greater than Carbon 3.

Ions 4.

Source Apportionment of PM2.5 Using a CMB Model for a Centrally Located Indian City

Organic Compounds 5. Inorganic Compounds 6. Physical and Optical Properties Several specific methods belonging to each category and the extent to which they meet the stated criteria are discussed here because of their widespread acceptance and use in the field of receptor modeling. Analytical methods not mentioned here should not be dismissed; they are also potentially useful. As the extent to which they meet the necessary and desirable criteria becomes known, their use for obtaining receptor model input data will increase accordingly. Elements X-ray emission spectroscopy Giaque et al.

More aerosol samples, numbering in the hundreds of thousands, have been analyzed by this method than by any other. In typical urban samples from 10 to 20 elements are routinely measured. Biases exist due to the attenuation of light element e.

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HIVOL samples on fibrous filters are inappropriate for this method because a portion of the aerosol penetrates beyond the filter surface and is collected within the volume of the filter material; the x-rays emitted by these particles are partially absorbed by the filter material. Spectral interferences of one element x-ray with another must be accounted for in the data reduction, but this is usually handled by the computer based spectrum processing routine Bonner et al, Interlaboratory and intermethod comparisons Camp et al.

Instrumental neutron activation analysis Zoller et al. It equals or surpasses x-ray emission in sensitivity for many elements and allows the quantification of a number of rare-earth elements not detectable by other methods.

Receptor Modeling for Air Quality Management (Data Handling in Science and Technology) Receptor Modeling for Air Quality Management (Data Handling in Science and Technology)
Receptor Modeling for Air Quality Management (Data Handling in Science and Technology) Receptor Modeling for Air Quality Management (Data Handling in Science and Technology)
Receptor Modeling for Air Quality Management (Data Handling in Science and Technology) Receptor Modeling for Air Quality Management (Data Handling in Science and Technology)
Receptor Modeling for Air Quality Management (Data Handling in Science and Technology) Receptor Modeling for Air Quality Management (Data Handling in Science and Technology)
Receptor Modeling for Air Quality Management (Data Handling in Science and Technology) Receptor Modeling for Air Quality Management (Data Handling in Science and Technology)
Receptor Modeling for Air Quality Management (Data Handling in Science and Technology) Receptor Modeling for Air Quality Management (Data Handling in Science and Technology)
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