Frequency Distributions of PM10 Chemical Components and Their

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Environ. Sci. Techno/. 1995, 29, 19-28

Frequency Distributions of PMlo Chemical Components and Their ALAN S. KAOt AND SHELDON K. FRIEDLANDER* Department of Chemical Engineering, University of California, 5531 Boelter Hall, Los Angeles, California 90024

The frequency distributions and statistical properties of the chemical components of PMlo and their sources in the South Coast Air Basin (SoCAB) were analyzed from several year-long studies. The nonreactive aerosol components of PMlo have approximately log normal frequency distributions and constant values of geometric standard deviation (GSD) regardless of source type and location. Some major components of PMlo behave differently from the total mass, resulting in a decreased variability for the total mass compared with the variability of the major components. The frequency distributions of the source contributions, as computed from a chemical mass balance (CMB) receptor model, showed approximately log normal behavior for most sources. There is evidence of bimodal frequency distributions for the crustal source of PMto at certain locations, possibly indicating contributions from several different sources that have similar chemical profiles.

Introduction The United States Environmental Protection Agency (U.S. EPA) is in the process of reviewing the National Ambient Air Quality Standard (NAAQS) for particulate matter (1). This review is important because of recent epidemiological studies that report increases in human mortality associated with levels of particulate pollution significantlylower than those previouslythought to affect human health (2). These studies suggest an association between nonaccidental mortalityandTSP, PMlo, or fine particle ( d p < 2.5pm) levels, but a mechanistic explanation for this link has not yet been established. Without knowing the causative agent, the US. EPA may be forced to revise downward the ambient particulate air quality standard, even though the scientific basis for making the decision is weak. Receptor models have played a major role in meeting current particulate standards. Receptor models are data analysis techniques that use ambient measurements of chemical species to apportion the contributions of various sources. These models assume the emissionsfrom different sources have characteristic chemical profiles. The differences in chemical composition among source emissions allow the contributions from each source type to be inferred. The most widelyused receptor model is the chemical mass balance (CMB) (3). The CMB requires only a few ambient measurements but also requires informationon the number of sources and chemical profiles of their emissions. Multivariate techniques, such as principal component analysis (4), have been developed that do not require detailed information on the sources. However, large amounts of ambient data are needed for these methods. California's South Coast Air Basin (SOCAB) has been classified by the EPA as a PMlo group I area, which is a designation for areas with greater than 95% probability of noncompliance with the federal particulate standard (5). The availabilityof extensive new data bases on the chemical composition of particulate matter collected from several SoCABlocations (Table 1)offers the possibility of extending the CMB technique to examine the time-series behavior of the sources of PMlo. Up to this point, time-series data have only been used with the CMB receptor model to determine annual average and seasonal source contributions (6-8). The current particulate standard is based on the total mass (PMlo)concentration. However, if a mechanism can be found linking a particular chemical component with the observed health effects, such as acid aerosols, the new standard may be based on that component. When evaluating the health effects of aerosol chemical components, it is important to realize that the chemical analysis of routinely collected particulate samples is not necessarily an accurate representation of the composition of the atmosphere. Many short-lived chemical species in the gas andlor aerosol phase, such as free radicals, are not present in sampled material at the time of chemical analysis. These unmeasured metastable species may be much more biochemicallyactive than the measured components and, therefore, could be responsiblefor the adversehealth effects associated with particulate mass (1). +

Present address: ENVIRON, 4350 North Fairfax Dr., Arlington,

VA 22203.

0013-935)(/95/0929-0019$09.00/0 0 1994 American Chemical Societv

VOL. 29, NO. 1 , 1995 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

'19

TABLE 1

Chemical Characterization Studies of Particulate Matter in South Coast Air Basin sampling period

location

measurement

Long Beach (LGB86) Hawthorne (HAW86) Burbank (BUR861 downtown LA (DLA86) Rubidoux (RUB861 Anaheim (ANH86)

Jan 2,1986-Jan 6,1987 24-h samples every sixth day

Duarte (DRT87)

June 12,1987-June 30,1988 8-h samples (12-8 PM) random sampling days

PMlo and

methodology

PM2.2

total mass trace elements s04*-,N 0 3 NH4+

organics PM3.5

total mass trace elements sod2-, NosNH4+

organics Jan IO, 1988-Jan 4,1989 24-h samples every sixth day

Rubidoux (RUB88) Magnolia (MAG881 Riverside (RIV88)

PMio

total mass trace elements sod2-,Nos-

NH4+

organics

PMlo sampler PTFE and quartz filters

gravimetric analysis XRF ion chromatography colorimetry thermal/optical reflectance high-volume sampler Teflon and quartz filters

ref

9, 10

11-13

gravimetric analysis PlXE

ion chromatography colorimetry evolved gas analysis (EGA) SCAQS sampler Teflon and quartz filters

31 6

gravimetric analysis XRF ion chromatography colorimetry thermal/optical reflectance

BURBANK DUARTE

0

-

0

%OWNTOWN

MAGNOLIA RIVERSIDE

PACIFIC OCEAN

o to

L.A.

2 0 30 km

FIGURE 1. Sampling sites in South Coast Air Basin (modified from ref 9).

Field Studies of PMlo in South Coast Air Basin Solomon et al. (9, 10) operated a monitoring network to measure the spatial and temporal distribution of atmospheric particulate matter in the SOCAB during 1986. Twenty-four hour samples of PMloand PM2.2 were collected every sixth day in Long Beach (LGB861, Hawthorne (HAW86), Burbank (BUR86), downtown Los Angeles (DLA86),Rubidoux (RUB86),and Anaheim (A.NH86). Duarte and Rubidoux, both inland locations that experience significant secondary aerosol formation, were the subjects of additional year-long studies. At Duarte (DRT871, 8-h fine particle (dp < 3.5 pm) saqples were collected on 61 approximately randomly selected days between June 1987 and June 1988 and analyzed as part of the Los Angeles Aerosol Characterization and Source Apportionment Study (LA-ACSAS) (11-13). In 1988,24-h samples of PMIOwere 20

ENVIRONMENTAL SCIENCE &TECHNOLOGY / VOL. 29, NO. 1 , 1 9 9 5

collected every sixth day at three neighboring (within 5 km of each other) sites: Rubidoux (RUB881, Magnolia (MAG88), and Riverside (RIV88) (6). The analytical techniques used in all of these studies are summarized in Table 1. The locations of these sampling sites are shown in Figure 1. The chemical characteristics of the PMlo data were discussed in detail by Solomon et al. (9, 10) and Chow et al. (6) and are summarized in Table 2. Average annual PMlo mass concentrations in 1986 ranged from 46.9pg m-3 at Hawthorne to 87.4 pg m-3 at Rubidoux. In 1988, the average annual PMlo mass concentrations in Rubidoux, Magnolia, and Riverside were 87.5, 66.3, and 63.4 pg m-3, respectively. All of the sampling sites except Hawthorne were in exceedance of the federal ambient annual average PMlo standard of 50 pg m-3.

TABLE 2

Summary of SoCAB Ambient Data: Average Total Mass, Variability d~(Standard DeviatioJMean Ratio), and PM2.dPMlo Mass Ratio PM10 mass

(/re m-?

fine particle mass (/rg m-s)

PMIo variability

location

fine particle variability (u/3

coarse particlea Variability (u/fj

PMulPMio mass ratio

LGB86 HAW86

52.3

30.6b 27.4b

0.44 0.48

BUR86 DLA86

56.6 60.2 87.4

0.49 0.45 0.56

0.44 0.44 0.40 0.44

RUB86

35.5b 36.5b 51.5b

0.72b 0.72b 0.74b

ANH86

52.1

28.4b 74.3c

0.47

0.556 0.549 0.588 0.593 0.609 0.517

46.9

DRT87 RUB88 MAG88

87.5 66.3 63.4

RIV88 a

2.2 pm

< dp