Using Multiple Criteria for Fingerprinting Unknown Oil Samples Having Very Similar Chemical Composition

This paper describes a case study in which a multi-criterion approach was used to fingerprinting and identifying mystery oil samples. Three unknown oil samples were received from Quebec on March 28, 2001 for chemical analysis. The main purpose of this analysis was to determine the nature and the type of the products, detailed hydrocarbon composition of the samples, and whether these samples came from the same source. The samples were analyzed by gas chromatography with a flame ionization detector (GC-FID) and by gas chromatography coupled with mass spectrometry (GC-MS). Hydrocarbon distribution patterns of unknown oils were recognized. Multiple suites of analytes were quantified and compared. A variety of diagnostic ratios of “source-specific marker” compounds for interpreting chemical data were further determined and analyzed. The chemical fingerprinting results reveal the following: (1) These three oils are most likely a hydraulic-fluid type oil. (2) These three oils are very “pure”, largely composed of saturated hydrocarbons with the total aromatics being only 4–10% of the TPH. (3) The oils are a mixture of two different hydraulic fluids. There is no clear sign indicating they had been weathered. (4) The PAH concentrations are extremely low (<10 μg/g oil) in the oil samples, while the biomarker concentration are unusually high (4700–5500 μg/g oil). (5) Three major unknown compounds in the oil samples were positively identified. They are antioxidant compounds added to oils. (6) Samples 2996 and 2997 are identical and come from the same source. (7) The sample 2998 has group hydrocarbon compositions (including the GC traces, TPH, and total saturates) very similar to samples 2996 and 2997. But, it is not identical in chemical composition to samples 2996 and 2997, and they do not come from the same source.     

A Strategy and Methodology for Defensibly Correlating Spilled Oil to Source Candidates

The source of crude oils and petroleum products released into navigable waterways and shipping lanes is not always known. Thus, the defensible identification of spilled crude oils and petroleum products and their correlation to suspected sources is a critical part of many oil spill assessments. Quantitative "fingerprinting" analysis, when evaluated using straightforward statistical and numerical analyses, provides a defensible means to differentiate among qualitatively similar oils and provides the best assessment of the source(s) for spilled oils. Polycyclic aromatic hydrocarbon (PAH) and petroleum biomarker concentration data are a particularly useful quantitative measure that can benefit most oil spill investigations. In this paper the strategy and methodology for correlation analysis that relies upon quantitative gas chromatography/mass spectrometry operated in the selected ion monitoring mode (GC/MS-SIM) is demonstrated in a case study involving 66 candidate sources for a heavy fuel oil spill of unknown origin. The strategy includes identification of 19 chemical indices (out of 45 evaluated) based upon PAH's and biomarkers that were (1) independent of weathering; and (2) precisely measured, both of which are determined by statistical analysis of the data. The 19 chemical indices meeting these criteria are subsequently analysed using principal component analysis (PCA), which helps to determine defensibly the "prime suspects" for the oil spill under investigation. The strategy and methodology described, which combines statistical and numerical analysis of quantitative chemical data, can be adapted and applied to other environmental forensic investigations with the objective of correlating any form of contamination to its suspected sources.     

A Strategy and Methodology for Defensibly Correlating Spilled Oil to Source Candidates

The source of crude oils and petroleum products released into navigable waterways and shipping lanes is not always known. Thus, the defensible identification of spilled crude oils and petroleum products and their correlation to suspected sources is a critical part of many oil spill assessments. Quantitative “fingerprinting” analysis, when evaluated using straightforward statistical and numerical analyses, provides a defensible means to differentiate among qualitatively similar oils and provides the best assessment of the source(s) for spilled oils. Polycyclic aromatic hydrocarbon (PAH) and petroleum biomarker concentration data are a particularly useful quantitative measure that can benefit most oil spill investigations. In this paper the strategy and methodology for correlation analysis that relies upon quantitative gas chromatography/mass spectrometry operated in the selected ion monitoring mode (GC/MS-SIM) is demonstrated in a case study involving 66 candidate sources for a heavy fuel oil spill of unknown origin. The strategy includes identification of 19 chemical indices (out of 45 evaluated) based upon PAH's and biomarkers that were (1) independent of weathering; and (2) precisely measured, both of which are determined by statistical analysis of the data. The 19 chemical indices meeting these criteria are subsequently analysed using principal component analysis (PCA), which helps to determine defensibly the “prime suspects” for the oil spill under investigation. The strategy and methodology described, which combines statistical and numerical analysis of quantitative chemical data, can be adapted and applied to other environmental forensic investigations with the objective of correlating any form of contamination to its suspected sources.     

Relationship between hydrocarbon measurements and toxicity to a chironomid, fish larva and daphnid for oils and oil spill chemical treatments in laboratory freshwater marsh microcosms

This research investigated the extent to which various common hydrocarbon measures can be used to predict toxicity to freshwater aquatic organisms due to fouling by oil. Actual toxicity results, on laboratory freshwater marsh microcosms using two water-column species and a benthic species, were described earlier. The hydrocarbon measures used were TPH(g), TPH(FID), TPH(MS), TTAH (sum of 41 target aromatic hydrocarbons), principal components of 41 TAHs, and each individual TAH. In general, toxicity was more closely related to TPH(MS) levels than to TPH(FID) and (especially) TPH(g) levels. The strongest relationships were found for TTAH levels and for the principal components of the TAHs. Regressions of toxicity on many individual TAHs were also strong, with a single group of compounds explaining as much as 59% of the variation in survival. While the various regressions were highly significant statistically and at times able to accurately predict broad differences in toxicity, the high variation in survival at a specific hydrocarbon concentration indicates that these hydrocarbon measures can not substitute for actual toxicity determinations in accurately ranking the toxicity of samples from oiled freshwater marshes.     

Bottom sediments of the Arabian Gulf--II. TPH and TOC contents as indicators of oil pollution and implications for the effect and fate of the Kuwait oil slick

Measurements of total petroleum hydrocarbon (TPH) concentrations in 77 core samples collected in 1992 from the bottom sediments of the Arabian Gulf were used to delineate oil pollution levels and their distribution in the region. Seven chronic moderately (TPH 50-89 microg g(-1)) and heavily (TPH 266-1448 microg g(-1)) polluted areas were identified; three in the northern part of the region and four in the southern part. Oil pollution in these areas was attributed to natural oil seepage, accidental damage to pipelines, accidental spillage from tankers, the Nowruz oil slick, and tanker deballasting. Present-day intermediate (TPH 50-114 microg g(-1)) and high (TPH 200-1122 microg g(-1)) pollution levels were identified in 10 areas. Of these, three polluted areas in the northeastern corner, offshore Saudi Arabia and offshore Bahrain, Qatar and United Arab Emirates are probably directly affected by the Kuwait oil slick. A new scenario is suggested for the movement and fate of the oil slick, in which additional large oil discharges from northern sources, as well as substantial quantities of eroded oiled sediments and oil floating from heavily impacted tidal flats along the Saudi Arabian coastline, serve as sources of oil pollution. A definite relationship exists between the grain-size distribution and the TPH content of bottom sediments, with the highest TPH concentrations in the muddy sediments, suggesting that adsorption onto muds is the primary mechanism of oil pollutant accumulation in the Arabian Gulf. Total organic carbon measurements do not correlate positively with the grain-size distribution and TPH contents of the sediments, and hence cannot be used as indicators for petroleum hydrocarbon pollution in the Arabian Gulf.     

Preliminary characterization and source assessment of PAHs in tributary sediments of the Athabasca River,Canada

The Athabasca Oil Sands are one of four natural oil sands deposits in Northern Alberta, Canada. As a number of new mines are planned in the area, there is a need to establish background levels of natural hydrocarbon release prior to these developments. To this end, various environmental samples were taken from selected tributaries in the oil sands region of the Athabasca River Basin and analysed by gas chromatography/mass spectrometry (GC/MS) for polycyclic aromatic hydrocarbons (PAHs) and their alkylated analogues. Samples were collected over 3 years (1998-2000) to provide an increased understanding of the spatial distribution, nature and extent of natural hydrocarbon release to the environment. Results indicated that levels of total PAHs were elevated in the tributaries (up to 34.7 µg/g) compared to the main stem Athabasca River (<2 µg/g). As expected, samples from the oil sands deposits contained the greatest amounts of PAHs and alkylated PAHs. Profiles of the alkylated PAM distributions were very similar, indicating that all the samples tested were from a common petrogenic source.     

Pyrolysis-GC-MS analysis of crude and heavy fuel oil asphaltenes for application in oil fingerprinting

A Pyrolysis – Gas Chromatography – Mass Spectrometry (Py-GC-MS) method was developed for the analysis and profiling of crude and heavy fuel oil asphaltenes, for application in oil fingerprinting. Asphaltenes were precipitated from ten geographically different oils using n-pentane, and analysed by Py-GC-MS. Alkane profiles and sulphur/aromatic profiles were used to compare the oils, and to correctly differentiate oils from different geographical regions. Py-GC-MS could not differentiate a weathered oil sample and a fresh oil sample from the same source. The results of this study support the findings from a previously developed FTIR method for asphaltene profiling.     

Fingerprinting of High Boiling Hydrocarbon Fuels,Asphalts and Lubricants

Fingerprinting of hydrocarbon products requires high resolution differentiation of individual hydrocarbon compounds in any mixture. This requires the applications of various measuring techniques. In this paper, we have chosen the heavy hydrocarbons in fuels, lubricants and paving material as examples to discuss the methods for chemical characterization and differentiation. In the category most frequently termed "semi-volatile hydrocarbons" with boiling points from about 500°F to 1200°F or higher, there are several families of hydrocarbons, both natural and refined that are not easily distinguished by conventional EPA tests. Among the groups which we will use as examples are asphalts, hydraulic fluid, transmission oil, motor lubricating oils, heating oils, crude oil and coal. These hydrocarbon families are best studied using combined gas chromatography-mass spectrometry in full scan mode and characterizing various homologous series of hydrocarbons at known fragment ions. The hydrocarbon series providing the best information are: (1) N -alkanes; (2) iso-alkanes; (3) steranes; (4) terpanes; (5) polynuclear aromatic hydrocarbons; (6) aromatic steranes; and (7) specific polycyclic compounds.     

Fingerprinting of High Boiling Hydrocarbon Fuels,Asphalts and Lubricants

Fingerprinting of hydrocarbon products requires high resolution differentiation of individual hydrocarbon compounds in any mixture. This requires the applications of various measuring techniques. In this paper, we have chosen the heavy hydrocarbons in fuels, lubricants and paving material as examples to discuss the methods for chemical characterization and differentiation.In the category most frequently termed “semi-volatile hydrocarbons” with boiling points from about 500°F to 1200°F or higher, there are several families of hydrocarbons, both natural and refined that are not easily distinguished by conventional EPA tests. Among the groups which we will use as examples are asphalts, hydraulic fluid, transmission oil, motor lubricating oils, heating oils, crude oil and coal.These hydrocarbon families are best studied using combined gas chromatography-mass spectrometry in full scan mode and characterizing various homologous series of hydrocarbons at known fragment ions. The hydrocarbon series providing the best information are: (1)N -alkanes; (2) iso-alkanes; (3) steranes; (4) terpanes; (5) polynuclear aromatic hydrocarbons; (6) aromatic steranes; and (7) specific polycyclic compounds.     

Aspects of Hydrocarbon Fingerprinting Using PLS-New Data From Prince William Sound

Partial least squares (PLS) techniques are used in the re-analysis of NOAA hydrocarbon data previously investigated in Mudge (2002). New data have been provided for coal and oil signatures and these have been investigated further. The effects of zeros (less than the limit of detection) in the dataset can be overcome by addition of small values at approximately half of this limit; this then enables logarithms to be taken of the entire dataset which greatly improved the usefulness of principal component analysis (PCA). Source samples collected close to each other had different signatures, probably due to their environmental histories which was also seen when aliphatic hydrocarbons were included in the signatures. Key compounds describing each could be seen in Coomans' Plots. Signatures developed from formation oils, riperian oils and coals from the eastern Gulf of Alaska (GoA) provided mean fits to subtidal samples within PWS of 22, 19 and 38% respectively. This suggests mixed and variable sources across the sampling area. The overall conclusion must be a question regarding the partitioning between oil and coal source materials as they look very similar in this particular location.     

Aspects of Hydrocarbon Fingerprinting Using PLS—New Data From Prince William Sound

Partial least squares (PLS) techniques are used in the re-analysis of NOAA hydrocarbon data previously investigated in 4. New data have been provided for coal and oil signatures and these have been investigated further. The effects of zeros (less than the limit of detection) in the dataset can be overcome by addition of small values at approximately half of this limit; this then enables logarithms to be taken of the entire dataset which greatly improved the usefulness of principal component analysis (PCA). Source samples collected close to each other had different signatures, probably due to their environmental histories which was also seen when aliphatic hydrocarbons were included in the signatures. Key compounds describing each could be seen in Coomans' Plots. Signatures developed from formation oils, riperian oils and coals from the eastern Gulf of Alaska (GoA) provided mean fits to subtidal samples within PWS of 22, 19 and 38% respectively. This suggests mixed and variable sources across the sampling area. The overall conclusion must be a question regarding the partitioning between oil and coal source materials as they look very similar in this particular location.     

代谢表面活性剂菌处理含油污泥的研究

试验采用异位生物修复技术堆肥法,对某炼厂油泥进行生物修复处理研究.用微生物代谢的表面活性剂对油泥进行预处理,洗脱油泥中部分油分后进行堆肥试验,投加从油田含油土壤中获得的以石油为唯一碳源、代谢高效生物表面活性剂的微生物C-2菌、F-2菌以及无机营养物和疏松剂(锯末),降解油泥中的石油污染物.经过外源微生物和内源微生物共同作用120 d,油泥中的石油烃总量由22 910 mg/kg下降到3 000 mg/kg以下.试验利用色谱-质谱联用方法分析了降解前后石油组分的变化.菌株经传统方法鉴定为蜡状芽孢杆菌、枯草芽孢杆菌.     

Oil Identification Based on a Goodness-of-Fit Metric Applied to Hydrocarbon Analysis Results

Assessment of environmental damage following accidental oil spills requires reliable oil identification methods. Results from hydrocarbon analyses of environmental samples are often difficult to interpret, because of the changes in oil composition (or weathering) that follows release into the environment, and because of confounding by hydrocarbons from other sources. To a first-order approximation, weathering proceeds according to simple first-order loss-rate (FOLR) kinetics for polycyclic aromatic hydrocarbons (PAH) based on molecular size. This relationship between relative weathering rate and molecular size can be exploited to infer the initial PAH composition of spilled oils, and this information can be combined with results for weathering-invariant analytes to substantially increase the precision and accuracy of hydrocarbon source recognition methods. The approach presented here evaluates a goodness-of-fit metric between the measured hydrocarbon composition of an environmental sample and a suspected source, after correcting for PAR weathering losses based on FOLR kinetics. Variability from analytical and sampling error may thus be accounted for, and source identifications can be expressed as objective probability statements. This approach is illustrated by application to four independent case studies.     

Fingerprinting of Gasoline and Coal Tar NAPL Volatile Hydrocarbons Dissolved in Groundwater

Accidental spills and chronic leaks of fuel oil or other hydrocarbon material (e.g., coal tar) often result in subsurface accumulation of nonaqueous phase liquid (NAPL), which can be a subsequent source of contamination in groundwater. Linking hydrocarbons in groundwater to a source NAPL has been difficult when using standard target analytes (e.g., BTEX) because of differences in partitioning properties of the analytes between the source NAPL and groundwater. Because aqueous solubility is predicted to be the controlling influence in the partitioning of hydrocarbons from NAPL to groundwater, a solubility-based approach to matching dissolved hydrocarbons in groundwater to their source NAPL has been developed and validated for two sites with commonly encountered types of NAPL contamination. Specifically, a gasoline LNAPL and a coal tar DNAPL from two separate sites (West Virginia and California) and groundwater interfaced with these NAPLs were analyzed for approximately 50 gasoline-range hydrocarbons consisting of paraffin, isoparaffin, (mono-) aromatic, naphthene, and olefin compounds (PIANO). Solubility characteristics of selected alkyl aromatic hydrocarbons from the PIANO analysis were used to identify a set of diagnostic hydrocarbons, expressed as hydrocarbon ratios, which were found to be useful in distinguishing the source(s) of hydrocarbons in groundwater. At the West Virginia site, the diagnostic ratios in a downgradient groundwater sample were similar to those of a gasoline NAPL at that site, indicating the source of hydrocarbons to the groundwater was the upgradient gasoline NAPL. The diagnostic ratios of the groundwater in contact with the gasoline NAPL and the remote groundwater were also similar, providing evidence that the diagnostic ratios were retained during transport in the aquifer. At the California site, diagnostic ratios in a cross-gradient groundwater sample differed from those of the coal tar NAPL at that site, indicating that the remote groundwater hydrocarbons did not originate from the coal tar contamination. Environmental factors such as selective degradation of specific isomers and various geological conditions (e.g., soil mineralogy, and organic content) may confound the application of this solubility-based fingerprinting approach. Thus, it is recommended that multiple diagnostic pairs be simultaneously evaluated when considering this fingerprinting approach for specific sites and product types.     

Oil Identification Based on a Goodness-of-Fit Metric Applied to Hydrocarbon Analysis Results

Assessment of environmental damage following accidental oil spills requires reliable oil identification methods. Results from hydrocarbon analyses of environmental samples are often difficult to interpret, because of the changes in oil composition (or weathering) that follows release into the environment, and because of confounding by hydrocarbons from other sources. To a first-order approximation, weathering proceeds according to simple first-order loss-rate (FOLR) kinetics for polycyclic aromatic hydrocarbons (PAH) based on molecular size. This relationship between relative weathering rate and molecular size can be exploited to infer the initial PAH composition of spilled oils, and this information can be combined with results for weathering-invariant analytes to substantially increase the precision and accuracy of hydrocarbon source recognition methods. The approach presented here evaluates a goodness-of-fit metric between the measured hydrocarbon composition of an environmental sample and a suspected source, after correcting for PAH weathering losses based on FOLR kinetics. Variability from analytical and sampling error may thus be accounted for, and source identifications can be expressed as objective probability statements. This approach is illustrated by application to four independent case studies.     

A field trial for an ex-situ bioremediation of a drilling mud-polluted site

The remediation of drilling mud-polluted sites in the Southeast of Mexico is a top priority for Mexican oil industry. The objective of this work was to find a technology to remediate these sites. A field trial was performed by composting in biopiles, where four 1ton soil-biopiles were established, one treatment in triplicate and one unamended biopile. Amended biopiles were added with nutrients to get a C/N/P ratio of 100/3/0.5 plus a bulking agent (straw) at a soil/straw ratio of 97/3. Moisture content was maintained around 30-35%. Results showed that, after 180 d, total petroleum hydrocarbon (TPH) concentrations decreased from 99300+/-23000mgTPHkg(-1) soil to 5500+/-770mgTPHkg(-1) for amended biopiles and to 22900+/-7800mgTPHkg(-1) for unamended biopile. An undisturbed soil control showed no change in TPH concentrations. Gas chromatographic analysis showed residual alkyl dibenzothiophene type compounds. Highest bacterial counts were observed during the first 30 d which correlated with highest TPH removal, whereas fungal count increased at the end of the experimentation period. Results suggested an important role of the straw, nutrient addition and water content in stimulating aerobic microbial activity and thus hydrocarbon removal. This finding opens an opportunity to remediate old polluted sites with recalcitrant and high TPH concentration.     

Improvement of the hydrocarbon phytoremediation rate by Cyperus laxus Lam. inoculated with a microbial consortium in a model system

Hydrocarbon phytoremediation by Cyperus laxus Lam. growing on perlite and inoculated with hydrocarbon-degrading microorganisms was evaluated. Total petroleum hydrocarbons (TPH) were extracted from weathered soil (60.7 g of TPH kg(-1) of dry soil) and spiked on perlite at initial concentration of 5 g of TPH kg(-1) of dry perlite. Phenological characteristics, total microbial viable counts, hydrocarbon degraders and residual hydrocarbons were determined through 180 days of culture. Phenological characteristics of inoculated plants were improved as compared with non-inoculated plants: root biomass was 1.6 times greater, flowering time was reduced (13%), and the number of inflorescences was 1.5 times higher. The rhizospheric bacterial and fungi counts were higher for planted treatments (inoculated and not inoculated) than for unplanted pots. The maximum phytoremediation rate (0.51 mg of TPH g(-1) of dry plant d(-1)) for inoculated plants was reached at 60 days of culture, and was two times higher than for non-inoculated plants (55% TPH removal). Similar hydrocarbon phytoremediation extent values for inoculated (90%) and non-inoculated (85%) plants were obtained at 180 days of culture. The present study demonstrated that mutual benefits between C. laxus and inoculated hydrocarbon-degrading microorganisms are improved during phytoremediation. It is pertinent to note that this is the first report of hydrocarbon phytoremediation by Cyperus laxus Lam., a native plant growing in highly contaminated swamps.     

Multidimensional gas chromatographic enantiomer quantification of some chlorinated xenobiotics in cod liver and fish oils.

Four chiral HRGC column systems for the separation of selected organochlor pesticides and photoconversion products (heptachlor, cis- and trans-chlordane, o,p'-DDT, o,p'-DDD, and alpha-HCH) were tested. Cod hver oil and fish oil samples from different countries were comparatively analyzed. Of all these columns, the fourth was the most suitable one for the analysis of the selected compounds. The enantiomer ratios [ER] of cis-chlordane, trans-chlordane, photodieldrin, alpha-HCH, and o,p'-DDD in fish oils are nearly 1.0, while the ERs of the same substances are significantly different from 1.0 in cod liver oils. Contrary to that, the ER values of o,p'-DDT are remarkable different from 1 in the cod liver oils as well as in the fish oils.     

An Assessment of Source Contributions to Ambient Aerosols in Central Taiwan

Ambient aerosols were sampled at three selected sites in the coastal region of central Taiwan to obtain composition data for use in receptor modeling. All the samples were analyzed for 20 elements with an x&#x0002D;ray fluorescence spectrometer. The mass percentage of sulfates in particle samples was determined by ion chromatography, and mass percentages of elemental carbon (EC) and organic carbon (OC) were determined by an elemental analyzer.

Because the three sampling sites were located within 25 km of each other, the average chemical compositions were similar for particle samples taken at the three sites on the same day. However, the variation in composition from day to day was significantly influenced by wind direction and change in local sources, such as the burning of agricultural wastes. The abundant species in the coarse fraction (2.5&#x0002D;10 µm) were Al (0.5&#x0002D;4.0 µg/m³), Cl (0.1&#x0002D;4.8 µg/m³), Ca (0.2&#x0002D;3.4 µg/m³), Fe (0.2&#x0002D;2.8 µg/ m³), and K (0.1&#x0002D;1.4 µg/m³), while the abundant species in the fine fraction (<2.5 µm) were S (0.3&#x0002D;3.5 µg/m³), Cl (0.01&#x0002D;1.9 µg/ m³), K (0.04&#x0002D;0.98 µg/m³), organic carbon (0.01&#x0002D;10.5 µg/m³), elemental carbon (0&#x0002D;10.7 µg/m³), and sulfates (1.2&#x0002D;15.7 µg/m³).

Calculations for source apportionment were carried out using the CMB7 software developed by the U.S. Environmental Protection Agency (EPA). The main sources for the coarse fraction of ambient aerosols in the region were found to be marine aerosol, coal and fuel oil combustion, burning

of agricultural wastes, and paved road dust. The main sources for the fine fraction were burning of agricultural wastes, diesel exhaust, coal and oil combustion, and sulfates. Source apportionment for the fine fraction was relatively sensitive to the types of sources selected for calculations and the compositions of the sources. The problem can be ameliorated by careful examination of possible sources and by use of local source profiles.     

An Assessment of Source Contributions to Ambient Aerosols in Central Taiwan

Ambient aerosols were sampled at three selected sites in the coastal region of central Taiwan to obtain composition data for use in receptor modeling. All the samples were analyzed for 20 elements with an x&#x002D;ray fluorescence spectrometer. The mass percentage of sulfates in particle samples was determined by ion chromatography, and mass percentages of elemental carbon (EC) and organic carbon (OC) were determined by an elemental analyzer.

Because the three sampling sites were located within 25 km of each other, the average chemical compositions were similar for particle samples taken at the three sites on the same day. However, the variation in composition from day to day was significantly influenced by wind direction and change in local sources, such as the burning of agricultural wastes. The abundant species in the coarse fraction (2.5&#x002D;10 µm) were Al (0.5&#x002D;4.0 µg/m³), Cl (0.1&#x002D;4.8 µg/m³), Ca (0.2&#x002D;3.4 µg/m³), Fe (0.2&#x002D;2.8 µg/ m³), and K (0.1&#x002D;1.4 µg/m³), while the abundant species in the fine fraction (&#x003C;2.5 µm) were S (0.3&#x002D;3.5 µg/m³), Cl (0.01&#x002D;1.9 µg/ m³), K (0.04&#x002D;0.98 µg/m³), organic carbon (0.01&#x002D;10.5 µg/m³), elemental carbon (0&#x002D;10.7 µg/m³), and sulfates (1.2&#x002D;15.7 µg/m³).

Calculations for source apportionment were carried out using the CMB7 software developed by the U.S. Environmental Protection Agency (EPA). The main sources for the coarse fraction of ambient aerosols in the region were found to be marine aerosol, coal and fuel oil combustion, burning of agricultural wastes, and paved road dust. The main sources for the fine fraction were burning of agricultural wastes, diesel exhaust, coal and oil combustion, and sulfates. Source apportionment for the fine fraction was relatively sensitive to the types of sources selected for calculations and the compositions of the sources. The problem can be ameliorated by careful examination of possible sources and by use of local source profiles.