Fossil- and bio-mass combustion: C-14 for source identification, chemical tracer development, and model validation

Nuclear Instruments and Methods in Physics Research B 92 (1994) 404-409 North-Holland

NOMB

Beam Interactions with Materials 8 Atoms

Fossil- and bio-mass combustion: C-14 for source identification, chemical tracer development, and model validation t L.A. Currie a**, G.A. Klouda a, D.B. Klinedinst D.J. Donahue ’ and M.V. Connolly d

a, A.E. Sheffield b, A.J.T. Jull ‘,

aNational Institute of Standards and Technology, Gaithersburg, MD 20899, USA b Chemistry Department, Allegheny College, Meadville, PA 16335, USA ’ NSF Accelerator Facility, University of Arizona, Tucson, AZ 85721, USA d Environmental Health Department, Albuquerque, NM 87103, USA

Carbonaceous gases and aerosols emitted during fossil- and bio-mass combustion processes have significant impacts on regional health and visibility, and on global climate. r4C accelerator mass spectrometry CAMS) has become the accepted standard for quantitatively partitioning individual combustion products between fossil and biospheric sources. Increased demands for source apportionment of toxic gases/vapors such as carbon monoxide and benzene, and toxic aerosol species such as polycyclic aromatic hydrocarbons, however, have led to increased needs for chemical source tracers. As a result, the application of atmospheric r4C measurements has been extended to the discovery of new chemical tracers and the validation of the related apportionment models. These newer applications of 14C are illustrated by recent investigations of: 1) sources of excessive concentrations of carbon monoxide and benzene in the urban atmosphere during the winter, as related to combustion source control strategies; and 2) the development/validation of potassium and hydrocarbon tracer models for the apportionment of mutagenic aerosols from biomass (wood) burning and motor vehicle emissions. Among the important consequences of these studies are new insights into potential limitations of elemental tracer models for biomass burning, and the impact of bivariate (isotopic, mass) chemical blanks on atmospheric 14C-AMS data.

1. Introduction Radiocarbon was introduced almost 40 years ago as a tracer for atmospheric carbon that would provide unique and quantitative discrimination between fossil and biospheric sources [l]. The potential of the method was greatly expanded when the required sample sizes were reduced from grams to milligrams of carbon, through the use of miniature gas proportional counters. The full potential was realized recently when the AMS revolution made possible the measurement of samples containing just micrograms of carbon. The capability of measuring the 14C/‘2C ratio in only 7 ug carbon with ca. 1% precision (standard uncertainty, ui) [2] means that excellent chemical, temporal, and spatial isotopic resolution can be applied to the study of transient atmospheric phenomena involving carbonaceous gases and particles, as well as quantitative appor-

* Corresponding author. Tel. + 1 301 975 3919, fax + 1 301 216 1134, e-mail [email protected]. ’ Contribution of the National Institute of Standards and Technology. Not subject to copyright. 0168-583X/94/$07.00

tionment of sources impacting health, visibility, and climate. The microgram capability for environmental i4C is inherent in the AMS technique, and is limited only by the efficient production of rugged targets with low overall blanks [3]. It makes possible the expansion of the range of applicability, beyond that of direct “dating”, to the apportionment of fossil/ biogenic sources and the calibration/validation of alternative tracer models. This enhanced capability may even lead to the discovery of new tracers (or chemical fingerprints) that can be applied to concentrations far below the microgram range of AMS, such as nanograms for classes of organic species such as polycyclic aromatic hydrocarbons (PAH), and femtograms for individual carbonaceous particles [3]. In the following sections we illustrate three such environmental applications, and offer two cautions: 1) adequate attention to the age and mass of the overall carbon blank, which is the ultimate limitation for 14C AMS; and 2) the danger of assuming that linear models and indirect (non-carbon) tracers remain valid for the full range of atmospheric conditions. Central to the three studies was the city of Albuquerque, NM, which suffers severe wintertime

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L.A. Currie et al. / Nucl. Instr. and Meth. in Phys. Res. B 92 (1994) 404-409

pollution episodes because of the fortuitous mix of meteorology, anthropogenic activity, and topography.

Parking Garaqe

2. Wintertime urban CO source contributions via 14C measurements - impli~tions for benzene source ap~~ionment Over the past decade during the winter, Albuquerque has failed to meet the United States Environmental Protection Agency’s (U.S. EPA) National Ambient Air Quality Standard (NAAQS) for CO (9 ppmv over 8 h). Results from emissions inventories indicate that the dominant sources are residential wood combustion (WC) and motor vehicle (MV) emissions [4]. These conclusions were supported by 1) a winter aerosol study (1984-85) using K and Pb as surrogate tracers to estimate CO ~ntributions from WC and MV emissions, showing a 25% WC contribution [S], and 2) 14C measurements of CO fractions from six samples that gave an estimated median WC contribution of 30% [6]. To comply with the NAAQS, several controls have been instituted, and by 1988 the number of exceedances dropped due to a cleaner vehicle fleet, the mandatory use of oxygenated fuels, and the implementation of designated no-bum days, based on meteorological forecasts 24 h in advance. In light of the implementation of no-bum days, a second 14C0 study was undertaken. 14C data from this latest (winter 1989-90) study gave estimated values of WC ranging from 0 to 31%, assuming that a measured t4C0 background component applies. For three samples representing forecasted stagnant days (no-bum) and the highest CO concentrations, estimated wood burning contributions ranged from 0 to 18%. Besides the quantitative apportionment of CO, this study gave an opportunity to investigate the hypothesis that 14C0 data may be useful for validating the current exposure risk model for mobile air toxics at roadway sites that simply relies on the average concentration ratio of CO to benzene from tail-pipe exhaust ]7]. Estimates of U.S. benzene emissions for 1988 allot 15% of the annual emissions to industriaf sources, 50% to biomass combustion, and 35% to auto (passenger cars) emissions [7]. Since comparable WC and MV benzene emissions are expected, concurrent concentration data on benzene were derived from the same canister samples prior to CO separation. The relation between benzene and fossil CO is shown in Fig. 1. The parking garage sample (m) is included to illustrate a point regarding the Occupational Safety and Health Administration (OSHA) Standard for benzene at 1 ppmv averaged over 8 h. If the OSHA standard should be reduced to 0.1 ppmv, consistent with the currently proposed revision of the American Conference of Governmental Industrial Hygiene (ACGIH) ~~~e~~~~ limit

II

Fossil &I (ppm by mokkction)

!

Fig. 1. Plot of wintertime benzene and fossil carbon monoxide concentrations (Albuquerque, 1989-90) for 8-h periods represented by day (06.30-14.30) and night (16.30-00.30) times. Parking garage sample was collected from 06.00 to 09.00 b. Standards are indicated for CO [National Ambient Air Quality Standard (NAAQS)], and benzene [Occupational Safety and Health Administration (OSHA); American Conference of Governmen~l Industrial Hygiene (ACGIH)].

value, it will approach levels seen here from non-industrial sources, e.g., WC and MV. In that case direct 14C data for benzene may be required to help discriminate between ambient and industrial contributions.

3. 14C for the apportionment of atmospheric mutagens: the Integrated Air Cancer Project In 1985 the U.S. EPA initiated the Integrated Air Cancer Project (IACP), a long term study to: 1) identify major airborne mutagens, 2) determine their emission sources, and 3) improve risk assessment data and methodologies for human exposure [S]. Winter air quality data from several cities indicated that most of the ambient aerosol carbon was contained in the respirable (< 2.5 p,m) size fraction and that the dominant sources of mutagenic carbonaceous material were motor vehicles and residential wood combustion. To test these hypotheses field studies were undertaken in U.S. cities having uncomplicated airsheds and aerosol carbon primarily from the above two sources, namely Raleigh, NC and ~buquerque, NM (1984-85), and Boise, ID (1986-87). A final study conducted in Roanoke, VA (1988-89), included a third combustion source, residential oil heating. A multiple linear regression (MLR) model that employed inorganic tracers, i.e., lead ” and soil-corrected potassium, was used to quantitatively apportion sources for both the aerosol carbon concentration and mutagenicity 191. 14C played the critical role of testing the validity of the indirect tracer model, since it gave

#’ In Roanoke, 2-methyl hexane served as the MV tracer, because of the diminished Pb content of gasoline. VII. OCEANS, ATMOSPHERE

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direct, absolute information for the MV (fossil) and WC (biospheric) components. In each of these cities, 12-h (07.00-19.00, 19.00-07.00) ambient samples were collected at residential and traffic intersection sites for appro~mately two months beginning in mid-November. AMS t4C data were obtained on samples of ca. 300-500 ug-C, with Poisson ET’Sof l-Z%. For most samples the dominant uncertain& (ca. 10%) was associated with the age of the wood model [lo] used to convert the 14C results to residential wood combustion contribution [lO,ll]. However, for a small subset the field blank was critically important (see section 3.2). 3.1. Isotopic, regression, and mutagen~i~ reszdts Comparisons of the average impacts of wood burning and motor vehicle emissions derived from the absolute (14C) isotopic tracer and multiple regression methods are given in Table 1, together with the wood and fossil source contributions to aerosol mutagenicity [12]. We see that the average concentrations found by the MLR and direct (14C) methods for MV and WC are consistent, which supports the validity of the elemental tracer model under these circumstances. In addition to the apportionment results, per se, a major objective of the study was to estimate mutagenic potency, i.e. the mutagenic effect per pg of MV vs. WC carbonaceous aerosol. Potency (rev/p,g-aerosol) is given by the ratio of the data in the last two columns of the table to the concentration data in the earlier columns. This measure shows the motor vehicle exhaust to be the more hazardous, as median potency results across all cities were approximately 3.4 rev/ug for the MV source, and 0.8 rev/ug for WC.

3.2. Impact

of the

blank on the quality of the data

The remarkable sensitivity of AMS makes characterization of the carbon blank of prime importance. Characterization in terms of mass-C and 14C/‘2C ratio in conversion to CO, and in target preparation is the first step; by 1) cornpositing combustion blanks and 2) running blank targets one typically finds that the carbon blank is contemporary (“living”) with a mass of a few tenths of a microgram to a few micrograms. When carrying out a field study, however, it is essential to pay attention to the impact of the entire measurement process on the nature of the blank. This was seen dramatically for the final locale of the IACP, Roanoke. Blank quartz filters were submitted to the contractor performing extractions of the aerosol organic matter, as part of the i4C quality control plan. AMS results for these blanks yielded a major surprise: both the carbon mass and isotopic composition varied over a large range, and they were strongly correlated (see Fig. 2a). Two observations follow immediately: 1) the blank mass and variation [70 + 33 (SD) p,g-C] are substantial compared to the typical sample mass [ca. 400 pg-Cl; and 2) the correlation structure implies a mixing phenomenon, involving two blank sources, one primarily contem~ra~, the other largely fossil. Assessment of the impact of such a bivariate blank on the uncertainty of the final radiocarbon results requires some special considerations. Careful attention must be given first to the full covariance structure of the blank; second, to the effect of the non-linear blank correction relation [Eq. (l)] on final uncertainty interval. Blank correction:

f,,,, = (fobs-fElhd/(l

- 4%) (1)

Table 1 Average ambient source contributions and mutagenicity of the IACP study cities City

Residential wood combustion

b.Wm31 14

Roanoke, VA Boise, ID ~buquerque, NM Raleigh, NC

Mutagenicity

Source Contribution a

C

b

11+1 17+2 16It3 _d

Mobile sources

ha/m31

Residential wood combustion [revertants/m3]

Mobile sources [revertants/m3]

MLR ’

14C

MLR

MLR

MLR

8.1 i-o.6 14 +2 15 *1 16 kl

5.2i0.9 6.OkO.6 8 *2 _d

4.ortro.5 6 +2 3 rtl 1 io.3

5.9+ 1.1 12 *3 19 *2 12 *1

10+1 ta+3 11*3 4+1

a Source contribution and mutagenicity are in units of ug extractable organic matter (EOM)/m3 for Roanoke and Boise, and pg carbon/m3 for Albuquerque and Raleigh. b Results based on t4C analysis (refs. [lO,ll] and those contained therein). Uncertainties are based on the standard uncertainties of the 14C measurements (weighted Poisson counting statistics) and the standard uncertainty of the ROM or carbon mass mean. Numbers of samples ranged from 13 to 44. ’ Results based on multiple linear regression (MLR) model (ref. [12], and those contained therein). Uncertainties are based on the MLR coefficient standard uncertainties. d Insufficient 14C data from mobile source sites.

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L.A. Currie et al./Nucl. Instr. and Meth. in Phys.Res. B 92 (1994) 404-409

0.0

1, I (, ,

0

20

,,,,,,, ,,, ,

, ,I

ml

no

40

60

80

Blank Carbon Mass (Pg)

of a new “molecular marker” to compensate for the loss of Pb as a tracer for motor vehicle aerosol [13]. The time series data for this third study consisted of ca. three weeks of diurnal measurements of the carbon isotopes and elemental tracers, as above, together with meteorological data and multivariate organic (PAH) aerosol data. As discussed in the previous section, 14C as the direct, absolute tracer for fossil and biomass burning aerosol is essential for the validation of the MLR model for MV/WC apportionment that uses Pb and K as indirect carbonaceous aerosol tracers. 4.1. Model validity Calibration/validation can be approached by comparing the WC and MV derived directly from the 14C aerosol data with that computed from the regression coefficients (&,, Px) of the MLR model. C(total carbon) = MV + WC = &,Pb

+ PxK + /3, (2)

0

0.2

0.4

0.6

0.8

ison SimulationResults

Fig. 2. (a) Roanoke bivariate filter blank (sample set 11, showing the correlation between radiocarbon “age” (fraction

of modern carbon) and blank carbon mass. (b) Asymmetric distribution resulting from error propagation of the bivariate blank through the non-linear correction relation for Roanoke ambient sample 50122.

wheref,,, is the corrected fraction of modern carbon; fobsthe observed value; fB the value for the blank, and 4B is the mass fraction of the blank, i.e. the mass of the carbon blank divided by the total carbon mass. Since normality is lost in error “propagation” through this non-linear relation, the final distribution is skewed, as shown in Fig. 2b. The message, for the application of AMS to small samples in “real” environmental studies, is that it is crucial to determine the level and bivariate structure of the overall carbon blank.

4. Application of 14C to determining the limits of model validity and identification of a new molecular marker A third, independent study taking advantage of the near ideal two-source urban “laboratory” (Albuquerque), performed in Dec. 1985, employed i4C for 1) the rigorous evaluation of the limits of the elemental tracer (K, Pb) linear model validity, and 2) the identification

(If the Pb and K tracers account for all carbon sources, then the expected value of the intercept /3, would be zero.) Calibration of the elemental tracer model is necessary because the p’s vary with time and location. Rapid withdrawal of leaded gasoline has caused &, to increase from 14 k 4 l.tg-C/kg-Pb in the earlier Albuquerque (IACP) study to 42 f 5 in the current study #*. The potassium coefficient depends on the wood burned. In Raleigh, PK was 110 f 8 pg-C/pg-K whereas in Albuquerque it was 206 f 11, based on simple regression of 14C-determined WC on K 1141. Attempts to fit a plane (Eq. (2)) to the C, Pb and K data failed. Analysis of residuals indicated that both the coefficients and the quality of fit differed between day and night. Also, PO was not statistically significant for the daytime fit (-0.2 f 2.2 kg-C), but carbon not accounted for by the MLR model was indicated by the nighttime fit (/3, = 10.5 * 3.0). At this point AMS 14C measurements on samples, containing as little as 30 kg-C, were critical. The resulting direct MV estimates were consistent with those based on Pb (&, Pb), but the direct WC estimates showed good agreement with those based on K (& K) only for the daytime samples. The direct, 14C tracer revealed that the lack of fit and excess carbon was associated with wood carbon, and that at least for nighttime aerosol carbon, potassium was not serving as a conservative tracer for biomass (combustion) carbon. For the most extreme case, the isotopic measurement showed a 65% excess of wood carbon over that estimated from the K coefficient.

x2 Note that all uncertainties given are regression coefficient standard errors (standard uncertainties). VII. OCEANS. ATMOSPHERE

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are important for the “extra” WC source at night, and the consequent decoupling of the non-volatile, noncarbonaceous tracer, potassium. Thus, AMS measurements of the urban carbonaceous aerosol, which were essential to indicate the nature of the MLR model breakdown, are now supported by some mechanistic understanding of the process.

4 “mdbn”

5. Summary

1

-4 4

-2

2

0 Principal Component

4

1

Fig. 3. Planar principal component projection of mass-normalized elemental and organic aerosol data, containing 92% of the variance. Symbols “D” and “N” indicate scores of day and (high concentration) night samples. The vectors indicate weights (loadings) for temperature (“temp”), and elemental (K, Pb) and organic variables, namely methyl dehydro ahietic acid (“mdha”) and benzdghilperylene (“bgp”). Note that “D” scores approximate a straight line parallel with the Pb-K axis, consistent with the two-source MLR model, while “N” samples have additional anticorrelation with atmospheric temperature.

4.2. Understanding the lack of fit; new tracer development

The wealth of multivariate data in this experiment made it possible to make some inferences about the causes of the MLR model failure. This is captured in a single principal component (PC) plot showing the relations among five variables and 12 samples reduced to two dimensions (Fig. 3) [13]. Interpretation is greatly aided by the fact that this two-dimensional projection of the original five-dimensional data contains essentially all of the information (92% of the variance). Looking first at the “D” (day) sample subset we see that it is approximately linear, which is consistent with a two-source (WC, MV) mixture model, described by Pb and K tracers, respectively. Alignment of the PAH combustion product “bgp” [benzo(ghi)perylene] suggests that this compound may serve as a practical Pb tracer substitute for mobile source aerosol. Also interesting is the dispersion of the “N” (night) samples toward the softwood pyrolysis product “mdha” (methyl dehydro abietane), in opposition to increasing temperature. This behavior is consistent with the 14C indication of excessive woodcarbon for nighttime samples, since mdha is a woodburning tracer, and it provides a basis for mechanistic inference. That is, since the semivolatile WC tracer mdha has the greatest abundance in the coldest, nighttime aerosol samples, it seems likely that volatility and gas-particle conversions

14C measurements of submilligram atmospheric aerosol samples have produced vital new information on sources of toxic and/or mutagenic gases and combustion aerosols. Apportionment of individual compounds (CO, C,H,) requires direct radiocarbon measurements of the isolated fractions. Indirect calibration/validation of surrogate tracers with 14C has been central in the application of the K, Pb MLR model to the apportionment of atmospheric mutagens in the Integrated Air Cancer Project. Finally, the limits of validity of the model were explored, with 14C contributing the critical insight that aerosol carbon not accounted for by the MLR model derived from woodburning. Incorporating this insight with a multivariate view of isotopic, elemental, meteorological, and organic data led to a mechanistic understanding and indicated a new, organic mobile source tracer. Two extremely important observations must be made from these atmospheric studies: 1) Rigorous attention to the overall blank, including age-mass covariance and error propagation through a non-linear relation, is essential for reliable application of AMS-14C to small environmental samples. 2) The assumed conservative tracer K, widely used to assess biomass burning, requires local wood-source calibration, and it may produce erroneous carbonaceous aerosol conclusions for certain temperature regimes.

References

[ll G.D. Clayton, J.R. Arnold and F.A. Patty, Science 122 (1955) 751.

La D.B. Klinedinst, A.P. McNichol, L.A. Currie, G.A. Jones, G.A. Klouda, K.F. von Reden, R.M. Verkouteren and R.J. Schneider, these Proceedings (6th Int. Conf. on Accelerator Mass Spectrometry CAMS-6), Canberra-Sydney, Australia, 1993) Nucl. Instr. and Meth. B 92 (1994) 166. [31 L.A. Currie, T.W. Stafford, A.E. Sheffield, G.A. Klouda, S.A. Wise, R.A. Fletcher, D.J. Donahue, A.J.T. Jull and T.W. Linick, Radiocarbon 31 (1989) 448. County Emissions Inventory [41 Albuquerque/Bernalillo from 1982 (revised 1984 and 1990). El W. Einfeld, M.D. Ivey and P.S. Homann, Sandia National Laboratories Rep. No. Sand88-0792/13 (1988).

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[7] [8]

[9] [lo]

Klouda, L.A. Currie, R.M. Verkouteren, W. Einfeld and B.D. Zak, J. Radioanal. Nucl. Chem., Art. 123(l) (1988) 191. W. Ollison, American Petroleum Institute, personal communication (1992). J. Lewtas and L.T. Cupitt, in: Proc. 1987 EPA/APCA Symp. on the Measurement of Toxic and Related Air Pollutants (19871 p. 555. C.W. Lewis, R.E. Baumgardner, R.K. Stevens, L.D. Claxton and J. Lewtas, Environ. Sci. Technol. 22 (1988) 968. G.A. Klouda, D. Barraclough, L.A. Currie, R.B. Zweidinger, C.W. Lewis and R.K. Stevens, in: Proc. 84th Annu. Meet. Air and Waste Management Association V15 (1991) paper 91-131.2.

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[ll] D.B. Klinedinst, G.A. Klouda, L.A. Currie and R.B. Zweidinger, Proc. 1993 U.S. EPA/AWMA Int. Symp. on Measurement of Toxic and Related Air Pollutants, Durham, NC (1993) p. 197. [12] C.W. Lewis, R.B. Zweidinger, L.D. Claxton, D.B. Klinedinst and S.H. Warren, Proc. 1993 U.S. EPA/ AWMA Int. Symp. on Measurement of Toxic and Related Air Pollutants, Durham, NC (1993) p. 207. [13] L.A. Currie, A.E. Sheffield, G.E. Riederer and G.E. Gordon, Atmos. Environ. 28 (1994) 1359. [14] L.A. Currie, in: Characterization of Environmental Particles, eds. J. Buffle and H.P. van Leeuwen, vol. I of the IUPAC Environmental Analytical Chemistry Series (Lewis, 1992) chap. 1, p. 3.

VII. OCEANS, ATMOSPHERE