Light Absorption by Primary Particle Emissions from a Lignite

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Environ. Sci. Technol. 1999, 33, 3887-3891

Light Absorption by Primary Particle Emissions from a Lignite Burning Plant T . C . B O N D , * ,† M . B U S S E M E R , ‡ B. WEHNER,‡ S. KELLER,‡ R. J. CHARLSON,§ AND J. HEINTZENBERG‡ Departments of Civil Engineering, Mechanical Engineering, Chemistry, and Atmospheric Sciences, University of Washington, Seattle, Washington, and Institute for Tropospheric Research, Leipzig, Germany

Anthropogenic aerosols from the burning of fossil fuels contribute to climate forcing by both scattering and absorbing solar radiation, and estimates of climate forcing by lightabsorbing primary particles have recently been published. While the mass and optical properties of emissions are needed for these studies, the available measurements do not characterize the low-technology burning that is thought to contribute a large fraction of light-absorbing material to the global budget. We have measured characteristics of particulate matter (PM) emitted from a small, low-technology lignite-burning plant. The PM emission factor is comparable to those used to calculate emission inventories of light-absorbing particles. However, the fine fraction, the absorbing fraction, and the absorption efficiency of the emissions are substantially below assumptions that have been made in inventories of black carbon emissions and calculations of climate forcing. The measurements suggest that nonblack, light-absorbing particles are emitted from low-technology coal burning. As the burning rate increases, the emitted absorption crosssection decreases, and the wavelength dependence of absorption becomes closer to that of black particles.

Background Light-Absorbing Aerosols in the Atmosphere. Anthropogenic aerosols from the burning of fossil fuels contribute to climate forcing by both scattering and absorbing solar radiation. [Forcing is defined as the change in radiative flux at the tropopause. Positive forcing refers to an increase in flux and hence a warming effect. Note that significant groundlevel flux changes may occur even when the top-ofatmosphere forcing is zero.] Charlson et al. (1) suggested that sulfate aerosols, which scatter incoming radiation, have a cooling effect that acts in the opposite direction to that of greenhouse gases, especially in industrial regions. However, light-absorbing aerosols absorb energy that would otherwise have been reflected to space, transferring heat to the atmosphere while reducing solar irradiance at the surface. * Corresponding author phone: (206)543-2044; fax: (206)685-3836; e-mail: [email protected]. † Departments of Civil Engineering, Mechanical Engineering, and Atmospheric Sciences, University of Washington. ‡ Institute for Tropospheric Research. § Departments of Atmospheric Sciences and Chemistry, University of Washington. 10.1021/es9810538 CCC: $18.00 Published on Web 09/18/1999

 1999 American Chemical Society

Recently, three-dimensional chemical transport models have been used to examine effects of light-absorbing aerosols (2, 3). The resulting three-dimensional maps of these aerosols have been used to infer optical properties of the atmosphere (3) or the climate-forcing contribution of light-absorbing aerosols (4, 5). The accuracy of these model results is dependent on an understanding of the emissions. Concentrations and column burdens are linearly affected by source terms, and the optical properties of absorbing aerosols are affected by their size, morphology, and chemical composition (6, 7). It is generally accepted that light-absorbing aerosols are primary particles produced directly from combustion of carbon-based fuels (8). Measuring characteristics of primary particles emitted from combustion sources is therefore a rational first step in understanding the atmospheric effects of light-absorbing aerosols. Emission Inventories. The anthropogenic emission of light-absorbing aerosols to the atmosphere has been estimated by combining fuel-use inventories with emission factors (2, 9). Several characteristics of the emissions are required for this process: the emission factor of particulate matter [EFPM, g (kg fuel)-1], the fine fraction (Ffine, the fraction of particulate matter with aerodynamic diameters below one micrometer), the absorbing fraction of fine particles (Fabs), and the wavelength-dependent absorption efficiency of the absorbing particles (Rabs(λ), m2 g-1) (10). While particles with diameters greater than 1 µm may also affect the radiation budget, it is commonly assumed that the short lifetimes of these particles prevent them from causing global-scale effects. The absorption emission index [EIabs, m2 absorption (kg fuel)-1] is the combination of these variables:

EIabs ) EFPMFfineFabsRabs

(1)

This value can be obtained from simple measurements at combustion sources (10), and it can provide a closure check on assumptions about those sources. The accuracy of model results can be no better than the degree of closure obtained at the source. Measurements or estimates of the emission factors and other characteristics have been published for coal burning (e.g. refs 2, 9, 11-15). However, the data, mostly taken in the United States, do not characterize the low-technology burning that is thought to be responsible for a large portion of the global burden of light-absorbing material. Furthermore, the measurements do not begin to account for the variation in emissions that results from differences in combustion practice. The net emission of light-absorbing carbon is determined by a balance between inception and growth of precursor particles and oxidative consumption of those particles (16). Both processes are temperature-dependent. At low temperatures, the net emission increases as the temperature rises, reaches a maximum, and then drops as the temperature increases further (17). For some combustion schemes, the temperature may be too low to produce any light-absorbing particles at all; gaseous fuels begin producing soot at around 1600 K (18). Yet it is the low-temperature applications that are currently thought to contribute a large fraction of the global black carbon inventory (e.g. ref 2). Clearly, measurements of low-technology combustion are needed to refine global inventories of black carbon. This paper describes results from an exploratory project in which optical properties and mass emissions were measured at a small heating plant burning lignite (brown coal or soft coal) in Leipzig, Germany during the summer of 1996. VOL. 33, NO. 21, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 1. Schematic drawing of the lignite combustor.

Method Source Description. The source measured was a small (2 MW) combustor, depicted schematically in Figure 1, that provided heat and hot water for a complex of buildings. Coal stored above the firebox was supplied to the combustor by a hydraulically operated gravity feeder. Both overfire and underfire air were supplied to the combustor; the underfire air and coal feed rate were was manually controlled, while the overfire air flow rate was constant. This technology is typical of heating plants in the former German Democratic Republic. The burner operated at full power during the early morning, and its output decreased as the steam demand was satisfied. Measurements taken at full power are representative of most of the fuel burned in this combustor on an annual basis, since the burner operates at full power during the winter. Real-time recording of the input rates of fuel and air was not possible, since only mechanical indicators monitored these rates. The concentration of CO2 in the exhaust increases with burning rate, since the overfire air flow never changed, and can be used as a surrogate for burning rate. Higher burning rates corresponded to active burning with a brightyellow, higher-temperature flame, while lower burning rates were sluggish, low-temperature combustion with a reddish color. Burning rates calculated by combining the CO2 concentration with exhaust velocity measurements correlate well with readings of the steam production rate, which were taken in the plant prior to each test. An analysis of the coal (Weyerhaeuser) revealed about 9% ash, of which 82% was attributed to Si, either in elemental form or as SiO2. The water content of the coal was about 40%; this high content is typical of lignites. Measurements. Sampling took place in the exhaust duct about 14 m downstream of the blower. The entire exhaust duct was below atmospheric pressure due to a large downstream fan that pushed the air through the chimney. Additional air drawn into the exhaust after the overfire air resulted in further dilution. We sampled the stack gas with a diluting probe to minimize coagulation of aerosol particles and condensation of water and to simulate atmospheric dilution. The dilution ratio was typically between 10 and 20, and the relative humidity in the sampling system remained below 60%. A preimpactor removed particles with diameters larger than 10 µm. We assessed the size dependence of absorption by alternating measurements with and without impactors for cut sizes ranging from 0.4 to 6 µm. We accounted for size-dependent particle losses in the sampling system by using a theoretical sampling efficiency, corroborated with cascade impactor measurements before and after the sampling system. Real-time data include the absorption coefficient measured with an absorption photometer (model PSAP, calibrated 3888

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to a wavelength of 550 nm, Radiance Research, Seattle WA), CO2 content (Horiba MEXA GE-534), and O2 content (read from the plant measurement, zirconium oxide sensor). Measurements with a differential-mobility particle sizer (DMPS) are described in a companion paper (19). The spatial variation of the absorption measured in the exhaust was much smaller than the time variation due to changes in combustion. Samples collected simultaneously on Nuclepore filters (polycarbonate membranes) were analyzed for absorption by light transmission measurements with a 4-wavelengthsoot-photometer and for mass by gravimetric measurements. A calibration factor to adjust these measurements to absorption by suspended particles was applied. Three of the Nuclepore samples were analyzed for graphitic carbon content by a Raman-spectroscopy method introduced by Rosen et al. (8) and refined by Keller et al. (20). Particles collected on the filters appeared brown, not black as would be expected if the particles were largely composed of graphitic carbon. We made three sets of cascade-impactor measurements in the exhaust (University of Washington Mark V) to determine the total emission of particulate matter and its size resolution. The cascade impactor measurements differed from the U.S. EPA “Method 5” procedure. We did not weigh particles deposited in the sampling inlet, but those large particles would have a negligible effect on climate because of their short atmospheric residence times. Neither did we collect condensable organic material after the gases had cooled, so the submicron PM measured by the cascade impactors is lower than that measured in the diluted sample. Measurements of absorption by particles collected on filters are known to be affected by the presence of scattering aerosols (21, 22). Extensive calibrations in our laboratory indicate that, for the PSAP, 2% of the scattering coefficient is measured as absorption. For Nuclepore filters, the artifact is 8% of the scattering (23). The measurements presented here have not been adjusted for that effect, since we did not measure light scattering. We estimate that the absorption coefficients presented here are biased high by about 1% for the PSAP measurements and 4% for the Nuclepore measurements.

Results and Discussion Combustion conditions were highly variable on both a daily and an instantaneous basis. Within a single 5-min period, a variation of 1-2% in the O2 content (measured after the overfire air) was common. Five-min averages of O2 content ranged from 9% to 15%. Characteristics of the emissions are found to depend on the combustion conditions. We assess this variation by summarizing results in three groups: tests taken at 65-80%, 80-90%, and 90-100% of full power. The divisions were chosen solely to separate our observations into bands of approximately equal width, and changing the divisions does not greatly impact the differences between groups. Results of the grouped measurements and overall averages for submicrometer particles are given in Table 1. The uncertainties listed in the table include measurement error and the observed variation. We also give results of analysis of variance (ANOVA) tests indicating whether differences between power groupings are statistically significant. Mass Emissions. The average emission factor and exhaust mass concentration of submicrometer particles, taken from measurements on Nuclepore filters in our sampling system, is 0.9 g kg-1. The mass concentration in the exhaust is about 50 mg m-3. The standard deviation of the measurements is about 50% of the average; the data in Table 1 suggest that submicrometer mass emissions may decrease as the burning rate increases, but the trend is not statistically significant because of the large variation in the observations.

TABLE 1. Summary of Emission Characteristics for Submicrometer Particlesa fraction of full power EFPM (g kg-1) mass concn (g m-3) absorption effic (m2 g-1) 450 nm 550 nm 750 nm 1000 nm power-law dependence EIabs < 1 µm (m2 kg-1)

90-100%

av

pb

65-80%

80-90%

1.4 ( 0.6 57 ( 26

0.9 ( 0.4 46 ( 23

0.6 ( 0.2 28 ( 11

0.9 ( 0.5 47 ( 21

0.14 0.49

0.62 ( 0.14 0.37 ( 0.08 0.17 ( 0.04 0.09 ( 0.03 2.5 ( 0.4 0.47 ( 0.12

0.54 ( 0.13 0.32 ( 0.08 0.15 ( 0.04 0.09 ( 0.04 2.3 ( 0.4 0.35 ( 0.16

0.44 ( 0.11 0.27 ( 0.07 0.14 ( 0.05 0.09 ( 0.03 1.7 ( 0.3 0.16 ( 0.07

0.54 ( 0.14 0.32 ( 0.09 0.15 ( 0.04 0.09 ( 0.03 2.0 ( 0.5 0.32 ( 0.18

0.01 0.02 0.46 0.99 0.09 0.04

a The error bounds include the observed variation (1 SD) as well as measurement error. b The p-statistic is the probability that the measurements do not differ between the three power fractions. For example, a value of 0.05 indicates that the variation between the fractions is statistically significant at the 95% level.

FIGURE 2. Mass size distribution from cascade impactor and DMPS tests. Size distributions from the cascade impactor measurements, including the mass obtained on a backup filter, are shown in Figure 2. A size distribution calculated from a representative DMPS scan is also shown on the graph for comparison. The in-stack cascade impactor tests provide the best estimate of total particulate matter, since the filter measurements, taken after the sampling probe and tubing, were more affected by losses of large particles. Table 2 summarizes the cascade impactor results; the emission factor for particles below 10 µm is about 5 g kg-1. This value is within the lower end of the range given by Hangebrauck for process heating (11); it is higher than the emission factor reported by EPA for an overfeed stoker but lower than that for a spreader stoker (12). For submicrometer particles, the single-filter averages are higher than the cascade impactor measurements by about a factor of 2. To identify the cause of the discrepancy, we undertook an extensive error analysis, considering indirect sources of error such as uncertainties in impactor cut size and sampling efficiency as well as direct measurement errors. The results of this analysis are included in the uncertainties in Tables 1 and 2. The two measurements still disagree because semivolatile material has the opportunity to condense in the diluted exhaust; to prevent condensation, dilution ratios need to be approximately 100:1 (24). Cascade impactor measurements, which were taken at exhaust temperatures of approximately 140 °C, do not include condensed material. From the cascade impactor measurements, the suggested value for the submicrometer fraction of particulate matter, Ffine, is about 12% with a large variation. The variation in Ffine results largely from deviations in the measurements of total

particulate matter. Estimates of the submicrometer mass based on combining the average values of total PM and Ffine have much greater uncertainties (90%) than do direct measurements (20%). If condensable material is to be considered as part of the climatically relevant aerosol, then the estimates of both EFPM and Ffine should be increased above the cascade impactor measurements. For the most accurate estimates, the dilution history of the sample should match that of the particles emitted to the atmosphere. This is not the case either for our samples or for samples taken according to the EPA Method 5 procedure, and we believe that the true value of the mass emission factor in the fine fraction lies between the cascade impactor and the single-filter measurements reported here. Absorption Efficiency and Graphitic Carbon. Table 1 lists the average absorption efficiency of the submicrometer emissions at four wavelengths, determined from absorption and gravimetric measurements on 13 Nuclepore filters. Values of Rabs are strongly dependent on the burning rate for light at 450 and 550 nm, while the changes in Rabs at 750 and 1000 nm are not statistically significant. The absorption efficiency given here is for the bulk emissions, not just the absorbing fraction, so the average value (0.32 ( 0.09 m2/g at 550 nm) is equivalent to the combination FabsRabs. This value is much lower than typical values of Rabs at visible wavelengths for black carbon (25). It is clear that Fabs (the fraction that absorbs light) is much lower than unity, or that the absorption efficiency of the absorbing material is much lower than typical values, or both. Absorption coefficients measured by the PSAP and by the Nuclepore at 550 nm are in good agreement. The measured values for each power fraction typically varied by about 10% of the average; the largest contributor to the uncertainty of these measurements is the calibration of the soot photometer (20%). Measurements of graphitic carbon determined by Raman scattering are given in Table 3 for three samples. The graphitic carbon mass fraction of the emissions is less than 2%, similar to previous findings of the elemental carbon fraction at a utility boiler (26). The sensitivity of the Raman method to substances polymerized between benzene and graphite has not been determined, so the graphitic carbon fraction given in Table 3 may overestimate the amount of GC present. An apparent absorption efficiency for the graphitic carbon is calculated for each sample by assuming that graphitic carbon is the only light-absorbing material present on the filters. This value is 19-39 m2 g-1, higher than either measured or predicted absorption efficiencies for BC. This finding suggests that a light-absorbing material other than graphitic carbon is present in the emissions. Spectral Dependence. For accurate radiative transfer modeling, the spectral dependence of absorption by particles VOL. 33, NO. 21, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 2. Results of Cascade Impactor Measurementsa no. 1 1-µm cutoff PM concn (mg m-3) EFPM (g kg-1) 10-µm cutoff PM concn (mg m-3) EFPM (g kg-1) submicron fraction percent of full power a

no. 2

no. 3

summary

21 ( 2 0.62 ( 0.10

31 ( 3

24 ( 2 0.39 ( 0.08

25 ( 6 0.50 ( 0.20

160 ( 7 4.8 ( 0.8 12%( 1% 60%

140 ( 10

280 ( 40 4.6 ( 0.7 8%( 1% 100%

230 ( 80 4.7 ( 0.7 12%( 10%

23%( 1%

Submicron measurements do not include condensable particulate matter.

TABLE 3. Measurements of Graphitic Carbon (GC) mass GC loading loading GC by rabs apparent rabs frac full (µg/cm2) (µg/cm2) mass (%) (m2/g) power (%) (m2/g GC)a 0.62 0.69 1.22 a

67 100 72

0.93 0.68 1.70

0.37 0.32 0.40

32 39 19

70 90 80

At 550 nm.

is needed. Measurements (27, 28) and theory (29) for particles small compared to the wavelength of light indicate that absorption efficiency is inversely proportional to wavelength as long as the complex refractive index is constant; that is, if Rabs ∼ λ-n, then n ) 1. If the complex refractive index varies so that absorption is stronger at shorter wavelengths, the exponent n becomes greater than one and the particles appear yellow or brown. Millikan (30) observed that this exponent increased nearly linearly with H/C atom ratio. In our measurements on submicrometer particles, the exponent n ranges from 0.8 to 3.0. The average value is 2.0, consistent with the yellow to brown appearance of these particles. The exponent becomes closer to the theoretical value for black particles (n ) 1) as the burning rate increases; effectively, the emissions become blacker. This change results from the decreasing absorption efficiency at 450 and 550 nm wavelengths. Several factors could contribute to deviations from the expected value of n ) 1: particle size, morphology effects, and the wavelength dependence of the refractive index. For particles that are large relative to the wavelength of light, Mie theory predicts that the wavelength dependence should decrease below n ) 1, so size effects cannot explain our results. Theoretical calculations of the optical behavior of fractal agglomerates find that the absorption acts as the sum of the component spherules as long as the fractal dimension is lower than 2 (31, 32); for freshly emitted BC, the fractal dimension is typically about 1.8 (33). Thus, if the component spherules were black, an agglomerate should also have a wavelength dependence of n ) 1. A wavelength-dependent refractive index could be responsible for the spectral dependence of these emissions. Dispersion theory for the visible region predicts that the refractive index of black carbon first decreases with wavelength and then increases (34, 35). Measured refractive indices exhibit a much smaller variation (36), and Mie calculations using those measurements predict a slight decrease in the predicted wavelength dependence of black carbon particles. We conclude that the wavelength dependence of the refractive index in these emissions must be stronger than that of black carbon, suggesting a brown component such as coal tar or incompletely aromatized carbon. The difference between these two is unclear, since coal tar typically contains 2-3 conjugated aromatic rings (37). The change in spectral dependence with burning rate could be caused by increased 3890

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FIGURE 3. Real-time variation of exhaust absorption coefficient and exhaust CO2 content. graphitization or oxidation of the organic material at higher temperatures. Absorption Emission Index. Absorption emission indices (EIabs) are calculated from the CO2 concentration and the PSAP measurements in the combustor exhaust. For submicrometer particles, the average value of EIabs is 0.32 ( 0.18 m2/kg fuel. For comparison, the combination of assumptions that have been used in global modeling yields an EIabs of 5.4 m2 kg-1, as noted previously (10). Most of the variation in EIabs results from changes in combustion conditions; the value of EIabs decreases by a factor of almost three from the lowest burning rates to the highest. In the real-time data, there is a significant negative correlation between CO2 and absorption coefficient, as Figure 3 shows for one test. The correlation coefficient between the average values of the CO2 and the absorption coefficient for 15 periods of about 8 min each was -0.73. Summarizing the effects of combustion conditions discussed here and in the companion paper (19): As the burning rate increases, the particle count increases; the particle size decreases; the total cross-section decreases; the wavelength dependence approaches that of blacker particles; the absorption efficiency decreases at shorter wavelengths, but does not change for longer wavelengths; and the total absorption emission decreases. The value of measuring EIabs directly is the elimination of the substantial uncertainty caused by combining the separate variables. The value of EIabs can be calculated as 0.2 ( 0.3 m2 kg-1 by combining the values of EFPM and Ffine from the cascade impactor tests and the value of (FabsRabs) at 550 nm from the Nuclepore measurements. Compared to the EIabs measured directly, the value is lower because of the low bias of the impactor measurements, but the uncertainty is almost twice as high. Combining values for the parameters from disparate sources, as is currently the practice, would result in even greater uncertainties.

TABLE 4. Size Resolution of Absorption and Mass size bin (µ m)

absorption frac

mass frac