Particulates source identification

Although Rs values of high Ks compounds derived from Eq. 3.68 may have been partly influenced by particle sampling, it is unlikely that the equation can accurately predict the summed vapor plus particulate phase concentrations, because transport rates through the boundary layer and through the membrane are different for the vapor-phase fraction and the particle-bound fraction, due to differences in effective diffusion coefficients between molecules and small particles. In addition, it will be difficult to define universally applicable calibration curves for the sampling rate of total (particle -I- vapor) atmospheric contaminants. At this stage of development, results obtained with SPMDs for particle-associated compounds provides valuable information on source identification and temporal... 

Kowalczyk GS, Gordon GE, Rheingrover SW. 1982. Identification of atmospheric particulate sources in Washington, D.C. using chemical element balances. Environmental Science and Technology 16 79-90. 

Neustadter, H. E., Fordyce, J. S. and King, R. B. (1976). "Elemental Composition of Airborne Particulates and Source Identification Data Analysis Techniques," Journal of the Air Pollution Control Association, 26, 1079. 

Although the ultimate source of much of particulate organic matter (POM) in the urban aerosol appears to be fossil fuel a specific knowledge of the amounts and classes of organic compounds contributed by various types of sources is lacking. Estimates of source contributions have been based on emission inventories which have been largely directed toward polycyclic aromatic hydrocarbons and/or benzo(a)pyrene. There has been very little work on the development of mathematical and statistical models for POM source identification and allocation (1). In view... 

Arditsoglou A, Samara C (2005) Levels of total suspended particulate matter and major trace elements in Kosovo a source identification and apportionment study. Chemosphere 59 (5) 669-678 (Original Research Article)... 

Scheff P, Valiozis C (1990) Characterization and source identification of respirable particulate matter in Athens, Greece. Atmos Environ 24 203-211... 

Airborne Particulates and Source Identification Data Analysis Techniques, /. Air Poliut. Control Assoc. (1976) 26,1079. 

Particle characterisation can be applied to both core samples and surface sediments to obtain information on the impacts of changes through time at a site or the impacts of contemporary emissions across a region, respectively. Such information is useful for policy formulation and in terms of targeted emission reductions, whether to protect a sensitive environment or the health of a population, source identification for airborne pollutants is vital. Supporting evidence can also be provided for long-range transport models as particulate sources may be identified from external sources (e.g. Davies et al., 1984). 

The major purpose of ambient particulate sampling is to obtain mass concentration and chemical composition data, preferably as a function of particle diameter. This information is valuable for a variety of problems effects on human health, identification of particulate matter sources, understanding of atmospheric haze, and particle removal processes. 

Vegetative burning was found to account for as much as 40% of the total particulate mass on cold winter days, or nearly 9% annually. This led to the identification of a source of 6500 tons/year of previously uninventoried emissions and prompted major efforts to reduce impacts from residential wood burning. 

Zweidinger, R. B., R. K. Stevens, C. W. Lewis, and H. Westburg, Identification of Volatile Hydrocarbons as Mobile Source Tracers for Fine-Particulate Organics, Environ. Sci. Technol., 24, 538-542 (1990). 

Rosen, H., A. D. A. Hansen, L. Gundel, and T. Novakov, 1978. Identification of the graphitic carbon component of source and ambient particulates by Raman spectroscopy and an optical attenuation technique, Appl. Opt., 17, 3859-3861. 

Smear or comminution techniques are enormously rewarding because they provide a wealth of informational detail without a large time investment. The methods are more suited to industrial applications and have found little application in the literature. The techniques necessarily disrupt the long range structure of a product but are well suited to the identification and enumeration of particulates such as crystals (Figure 1), or the structure and microchemical composition of proteinaceous particulates, either of which can be the source of organoleptic issues such as graininess. 

PMF has successfully been applied to data from aerosol mass spectrometers (AMS, Aerodyne Research Inc., Billerica) for identification of the main sources of particulate organic matter, OM [9,12, 39], AMS instruments allow measurement of the mass spectra of the non-refractory fraction of approximately PM1 with high temporal resolution and determination of the concentration of particulate OM, which can be converted to OC by multiplication by a conversion factor [40]. 

It should be remarked that the application of CA is not limited to the description of the impact of particulate emissions. BIRRING and HASWELL [1994] describe the use of both CA and PCA for the identification of different sources of biogases. 

Commonly the compromising conditions of routine environmental monitoring lead to restrictions on the accuracy and the precision of sampling and analysis. The purpose of this section is to show that under these conditions multivariate statistical methods are a useful tool for qualitative extraction of new information about the degree of stress of the investigated areas, and for identification of emission sources and their seasonal variations. The results represented from investigation of the impact of particulate emissions can, in principle, be transferred to other environmental analytical problems, as described in the following case studies. 

Evaluation of the primary and secondary components of aerosol OC have been difficult. Lack of a direct chemical analysis method for the identification of either of these OC components has led to several indirect methods. The simplest approach to estimating the contributions of primary and secondary sources to measured particulate OC is the EC... 

The sensibility of lichens to atmospheric pollution was demonstrated in the last two decades in various international and national publications. Recent studies showed that the survey of a large territory with lichens turns identification of atmospheric pollution sources possible (Sloof, 1993). The use of lichens is the only possibility to go through a large scale monitoring, which otherwise would be done with an enormous amount of air samplers and samples. Response of lichens to the environment is being studied through modelling very recently in our Institute (Reis et al., 1999). This is made with lichen transplants whose response to airborne particulate matter, and total deposition is followed experimentally. 

As with all atmospheric species, trace metal emissions undergo atmospheric transport and dilution before they reach a particular receptor site. Mathematical models can be constructed based on the fundamentals of atmospheric chemistry and physics that will track the contributions from many emission sources as they undergo atmospheric transport. Indeed, the development of such models will receive considerable attention in this book. In the case of particulate emissions, an alternative is available. It is possible to attack the source contribution identification problem in reverse order, proceeding from measured particulate concentrations at a receptor site backward to the responsible emission sources (see Chapter 24). The unique metals content of the emissions from each source type is viewed as a fingerprint for the presence of material from that source in an ambient aerosol sample. 

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