Review of the IMPROVE Equation for Estimating Ambient Light Extinction

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Review of the IMPROVE Equation for Estimating Ambient Light Extinction Jenny Hand 1 Bill Malm 2 1 CIRA, Colorado State University 2 National Park Service

OUTLINE Introduction Sampling Biases Chemical forms of species in IMPROVE equation Mass scattering efficiency- methods for deriving and recent literature survey

Recall: PM 2.5 = (NH 4 ) 2 SO 4 + NH 4 NO 3 + POM + LAC + Soil Soil = 2.2Al + 2.49Si + 1.94Ti + 1.63Ca + 2.42Fe POM = R oc OC

Recall: Light extinction includes contributions from gases and particles b ext = b sp + b ap + b sg + b ag b sp = 3.0f(RH)[(NH 4 ) 2 SO 4 ] + 3.0f(RH)[NH 4 NO 3 ] + 4.0R oc [OC] + 1.0[Soil] + 0.6[CM] b ap = 10.0[LAC]

Aerosol Species measured by IMPROVE Module A ( 2.5 µm) B ( 2.5 µm) C ( 2.5 µm) Substrate Teflon Nitric acid denuder plus nylon filter Prefired quartz substrates Measured Variables Fine mass, Elements NO 3-, NO 2-, Cl -, SO 4-2 Organic and elemental carbon D ( 10 µm) Teflon Total mass Nephelometers (b sp ) at ~24 sites and Transmissometers (b ext ) at ~14 sites

BIASES Artifact: any increase or decrease in the material being sampled that results in a positive or negative bias in the ambient concentration measured Positive: contamination, adsorption of gases on filter Negative: volatilization of gases from disassociated particles on the filter medium (during sampling or handling) Biases affect aerosol species differently; applying corrections is not always straightforward

BIASES Corrections to IMPROVE data for sampling artifacts have been applied as part of routine methodology since 1988 Dynamic field blanks for Teflon and nylon filters are collected at all sites by being placed in the sampler with no air drawn through Teflon field blanks are insignificant- no corrections Nylon field blanks- concentrations are subtracted from measured filters (monthly median artifact corrections applied separately for each ion) Quartz after-filters are collected at 6 sites- designed to capture organic gases (positive artifacts)

BIASES: Nitrate (NO 3- ) NO 3 - sampled with nylon filters (corrections < 10 %, McDade et al., 2004) Denuders precede the filters to capture acidic gases (HNO 3 ); positive artifacts could occur if the denuder efficiency degrades with time Recent studies suggest that no differences in nitrate concentrations were observed due to different denuder configurations (Ashbaugh et al., 2004; Yu et al., 2005a) Nitrate loss from Teflon filters remains an issuedisassociation of NH 4 NO 3 particles- Teflon does not retain nitrate as nylon filters do-important implications for gravimetric mass

BIASES: Ammonium (NH 4+ ) Recent work by Yu et al. (2005b at 4 IMPROVE sites NH 4 + losses ranging from 9.7% - 52% Disassociation of NH 4 NO 3 : nitrate is retained but NH 4 + is not N-N and T-N performed about the same PM2.5 HNO 3 Denuder NH 3 Denuder N Filter (H2O) N Filter (IC) PM2.5 HNO 3 Denuder NH 3 Denuder Teflon Filter (H20) N Filter (IC) NH 3 Denuder NH 3 Denuder

BIASES: Carbonaceous aerosols Carbonaceous aerosol concentrations are determined with the DRI thermal/optical reflectance (TOR) technique Organic carbon (OC) is separated into fractions based on temperature regimes in the measurement protocol (O1, O2, O3, O4, OP) Elemental carbon (LAC) determined in the high temperature regime (E1, E2, E3) OC/EC split is method dependent

BIASES: Carbonaceous aerosols Sampling carbonaceous particles is tough Positive artifacts due to adsorption of organic acids on the filter Negative artifacts occur due to volatilization of particulate organics Artifact contributions to organic mass can range from -80 % to + 50 % (Turpin et al., 2000). Huebert and Charlson (2000) suggest systematic errors on the order of ±80 % are possible with thermal methods

BIASES: Carbonaceous aerosols IMPROVE network assumes negative artifacts are insignificant Positive artifacts: estimated from quartz after-filters at 6 sites, determined separately for each fraction of OC and EC O3 artifact represents nearly half of ambient concentration E2 artifact is less than 10 % of ambient concentration (since 2000) McDade et al. (2004) Some spatial and seasonal differences: -Okefenokee site has higher O3 artifacts than the other sites -Summer has higher O3 and E2 artifacts than winter The same median value is applied to the entire network

BIASES: Coarse mass and elemental species Elemental species are determined by XRF Lower Z elements have higher MDLs CM = PM 10 PM 2.5 Uncertainties in flow rates can significantly affect coarse mass as well as fine mass (more later)

CHEMICAL FORMS: Particulate Organic Matter (POM) POM = R oc [OC] Current algorithm: R oc = 1.4 (Based on measurements from the late 70s in Pasadena, CA) R oc (as suggested by Turpin and Lim, 2001) 1.6±0.2 for urban organic aerosols 2.1±0.2 for non-urban organic aerosols 2.2-2.6 for samples with biomass burning influences

CHEMICAL FORMS: Particulate Organic Matter (POM) Observations: Biomass burning observations: R oc ~ 1.8 (aged) (Malm et al., 2005; Poirot and Husar, 2004) Fresh smoke R oc ~ 1.1-1.2 (Day et al. 2005) El Zanan et al. (2005) performed extractions on IMPROVE filters from 5 sites (1998-2000): estimated R oc from these data ranging from 1.58±0.13 (Grand Canyon) to 2.58±0.29 (Mount Rainier) Average: 1.92±0.40 (Median 1.78)

CHEMICAL FORMS: Estimating R oc PM 2.5 = a 1 [(NH 4 ) 2 SO 4 ] + a 2 [NH 4 NO 3 ] + a 3 [OC] + a 4 [LAC] + a 5 [Soil] + a 6 [sea salt] Issues: chemical forms of species (e.g., ammonium sulfate, soil) water retention on Teflon filter sampling artifacts collinearity

Annual average R oc factor 2.58±0.29 * 1.78±0.18 * 1.58±0.13 * 2.01±0.34 * 1.64±0.31 * * El-Zanan et al., 2005

Seasonal variation in Roc

CHEMICAL FORMS: Nitrate a2 = 0.8 ± 0.3 HNO 3 (g) + NH 3 (g) NH 4 NO 3 (p) HNO 3 (g) + NaCl(p) NaNO 3 (p) + HCl(g) 2 HNO 3 (g) + CaCO 3 (p) Ca(NO 3 ) 2 (p) + CO 2 + H 2 O coarse particles

Fine Nitrate (D p < 1 µm) Data courtesy of T. Lee (Lee et al., 2004)

Fine Nitrate (D p < 3.2 µm) Data courtesy of T. Lee (Lee et al., 2004)

Coarse Nitrate (D p > 1 µm) 1 7 % 1 2 % 2 4 % 6 4 % 6 4 % 3 0 % 2 % 7 7 % 6 % 4 4 % 2 4 % 3 6 % 3 2 % 6 4 % 6 9 % 2 9 % G r e a t S m o k y M o u t a i n s ( s u m m e r ) 3 8 9 n3 g / m 9 1 % Data courtesy of T. Lee (Lee et al., 2004) ( N 4N H ) 3 O N a N3 O C a ( 3) N 2 O

CHEMICAL FORMS - Sulfate a1 = 1.2 ± 0.2 Fully neutralized ammonium sulfate is assumed SO 4-2 -2 as (NH 4 ) 2 SO 4 : 1.375 [SO 4 ] -2 as (NH 4 ) 3 H(SO 4 ) 2 : 1.29 [SO 4 ] -2 as NH 4 HSO 4 : 1.2 [SO 4 ] NH 4 + is not measured regularly at IMPROVE sites More acidic forms of sulfate have been measured at many locations

CHEMICAL FORMS- Soil a5 = 1.2 ± 0.3 Soil composition varies as a function of location and is further complicated by intercontinental and transcontinental transport (Asia, Africa, Mexico) Soil mass concentrations are computed by assuming oxides of elements typically associated with soil

Annual average soil coefficient a5 = 1.2 ± 0.3

CHEMICAL FORMS- Coarse mass CM = PM 10 PM 2.5 Coarse mass speciation at nine IMPROVE sites in 2003 for ~ year Preliminary results: over 50 % of CM is soil, with higher soil concentrations in the west than east POM is next highest contributor (15-35 %)- homogeneous spatial distribution Nitrate (5-15%) associated with sea salt on the coast Sulfate is minor except at some coastal sites in NE (~ 10 %)

CHEMICAL FORMS- sea salt a6 = 1.12 ± 0.5 Sea salt is not currently included in the IMPROVE algorithm Usually computed from sea salt markers like Na +, Cl - or combinations Difficulties arise because positive ions are not analyzed as part of the IMPROVE network, elemental Na data have large uncertainties, depletion of Cl due to reactions of HNO 3 with sea salt Could be important at coastal sites Compute from 1.8 Cl - (sea salt is 55 % Cl by weight)

Methods for deriving mass extinction efficiencies (α ext, m 2 g -1 ) Measurement method Theoretical method Multi-linear regression method (MLR) Partial scattering method

Measurement method Specific mass scattering efficiency can be defined as the ratio of light scattering coefficient (b sp ) to mass concentration (M): αsp _ spec = b sp M Either the average b sp is divided by the average mass, or a linear regression is performed on the data and the slope is interpreted as the specific mass scattering efficiency Represent an average aerosol that could be changing due to variations in RH, size distribution and composition

Theoretical method b ext α = ext 0 = α ext 3 2 Q dm d d log Dp ext ( n, ρ p D D p p log, λ) Dp ρ p =particle density λ=wavelength of incident light Q ext =Mie extinction efficiency D p = particle diameter

Multi-Linear Regression method (MLR) b ext = Σα Mj M j Assumptions: All aerosol components (M j ) contributing to b ext are included large number of samples uncorrelated species (collinearities) biased by random uncertainties in measurements: species with lower uncertainties are over-predicted and vice-versa

Partial Scattering α ext, part = b ext M j Depends on change in concentration as species M j is added or removed- either by changing particle number or size useful for regulatory purposes, difficult to implement in practice

Literature Survey ~ 60 peer-reviewed journal articles since 1990: focus on ground-based measurements Results separated into methods used, also for species and size modes Corrections to sulfate and POM applied

Barrow, AK Fine mode (m 2 g -1 ) 2.5 0.82 4.26 4.19 3.67 3.0 3.45 4.3 4.21 2.4 2.5 2.53 1.72 2.37 Theoretical MLR Measurement Partial 2.1 2.4 2.5 2.2 1.91 1.89 3.4 2.23.0 2.01.5 4.5 2.3 3.7 3.1 3.8 4.1 3.9 6.0 7.6

Coarse mode (m 2 g -1 ) 0.27 0.52 1.9 1.7 0.54 0.28 Theoretical MLR Measurement 0.07 0.62 0.8 0.28 0.6

Dry Fine (NH 4 ) 2 SO 4 (m 2 g -1 ) 1.5 3.1 2.7 2.6 3.2 2.03 8±3 2.2 2.08 2.23 3.3 2.2 3.4 2.1 4.0 5.2 2.9 3.05 2.63 2.8 2.4 Theoretical MLR Measurement Partial 2.96 1.47

Fine POM (R oc =1.8) (m 2 g -1 ) 1.8 2.61 2.7 2.4 1.5 2.07 0.82 1.4 0.7 3.11 2.2 5.9 8±5 1.7 2.0 Theoretical MLR Partial

Fine Dust (m 2 g -1 ) 2.3 2.4 2.6 5±2 0.7 3.1 1.76 2.06 0.79 2.1 4±3 4.2 1.8 Theoretical MLR Partial

Global Fine Mode (m 2 g -1 ) 5.1 4.8 3.0 3.7 5.85.2 4.5 3 4 4.3 3.6 4.3 2-5 1.65 3.2 Theoretical MLR Measurement

Global Coarse Mode (m 2 g -1 ) 0.12 0.34 0.5 1.4 0.87 1.02 0.6 2.4 Theoretical MLR

Global Total Mode (m 2 g -1 ) 1.4 1.2 1.84 1.03 2.3 2.5 Theoretical Measurement

Global Fine Dry (NH 4 ) 2 SO 4 (m 2 g -1 ) 3.9 0.9-3.3 4.6 6.0 3.4-4.1 2.5 1.83 2.1 1.6 1.12 Theoretical MLR

Global Fine POM (R oc =1.8) (m 2 g -1 ) 2.9 4.7 7.2 5.4 Theoretical

Global Fine Dust (m 2 g -1 ) 3.4 3.6 3.4 2.73 Theoretical MLR

Global Coarse Dust (m 2 g -1 ) 0.45 0.34 0.48 0.64 0.67 0.60 0.80 Theoretical MLR

Global Total Dust (m 2 g -1 ) 0.77 0.52 1.07 0.71 1.2 1.1 1.5 0.9 0.51 Theoretical MLR Measurement

Global Fine Sea Salt (m 2 g -1 ) 2.2 5.0 4.95 6.0 5.5 4.1 Theoretical MLR

Global Coarse Sea Salt (m 2 g -1 ) 2.9 1.3 1.6 0.90 1.12 1.06 Theoretical MLR

LAC (m 2 g -1 ) (corrected to λ=550 nm) 19.5 16.4 12.85 10.2 12.4 13.5 4.5 14.4 10±5 10.3 1.7-7.3 Theoretical MLR Measurement Partial 13.0 5.3-18.3

Global LAC (m 2 g -1 ) (corrected to λ=550 nm) 8.0 6.5 19.2 28.8 32 8.9 10-20 8.5 8.8 10.5 Theoretical MLR Measurement

Summary of Mass Scattering Efficiencies from All Methods (m 2 g -1 ) Species/mode Theoretical MLR Partial IMPROVE Fine 4.3 ± 0.7 (26) Coarse 1.6 ± 1.0 (21) Total 2.2 ± 1.0 (9) Sulfate 2.5 ± 1.1 (16) 3.1 ± 1.5 (17) 0.7 ± 0.6 (13) 3.2 ± 1.2 (24) Nitrate 4 ± 2 (16) POM 5.9 ± 1.0 (20) Fine dust 3.4 ± 0.5 (19) Coarse dust 0.7 ± 0.2 (21) Total dust 1.2 ± 0.3 (9) Fine sea salt 5.3 ± 0.8 (22) Coarse sea salt 1.2 ± 0.3 (20) Total sea salt 2.3 ± 0.9 (9) 2.3 ± 1.0 (23) 3 ± 2 (19) 0.40 ± 0.08 (2) 0.7 ±0.2 (3) 4.0 ± 1.6 (3) 1.6 ± 1.2 (3) 2.2 (1) 2.8 ± 0.7 (24) 3.8 ± 1.6 (11) 5.4 ± 1.8 (26) 3 ± 1 (9) 0.6 3 3 4 1

Discussion

Species density Refractive index RH(D) RH(E) (NH 4 ) 2 SO 4 1.76 1.53 80 37-40 (NH 4 ) 3 H(SO 4 ) 2 1.83 1.51 69 35-40 NH 4 HSO 4 1.78 1.473 40 0.05-20 H 2 SO 4 1.8 1.41 - - NH 4 NO 3 1.725 1.554 62 25-32 NaNO 3 2.261 1.587 74.5 0.05-30 NaCl 2.165 1.544 75.3 46-48 Na 2 SO 4 2.68 1.48 84 57-59

Global Total Sea Salt (m 2 g -1 ) 0.52 2.8 1.6 2.2 1.7 1.6 Theoretical MLR

Annual average sea salt coefficient