The Assessment of Emission Analysis Accuracy

An assessment of the accuracy of emission measurements is fundamental to an understanding of the ability of an organization to comply with emission regulations. Without a knowledge of the measurement accuracy, the significance of observed differences cannot be assessed. In addition, the average emission level that a group of engines must achieve for compliance is a function of the accuracy of the measurement of the exhaust constituents; i.e., the less accurate the measurement, the lower the average level must be to assure that essentially all engines pass the compliance tests. The accuracy assessment specifically included: 1) test instrument precision, 2) calibration gas accuracy and 3) sample error due to the distribution of data resulting from gas concentrations that are spatially non-uniform. In addition, the accuracy assessment required the consideration of the following general topics: the propagation of errors in a calibration hierarchy, the proper choice of error units, surveys of instrument precision, the evaluation of the significance of various instrument errors, the assessment of the significance of sampling error, and the consideration of methods for demonstrating representative samples and improving instrument precision. An accuracy assessment considering those factors resulted in the following conclusions: 1) Emission instrument precision is best expressed as percent of full scale. 2) The proper units for bias errors are percent of point. 3) Calibration-to-calibration repeatability may be utilized to estimate instrument precision. 4) Instrument precision shows wide variations from day to day. 5) Correcting past data by post-test calibration adjustments will not, in general, improve emission data altered by instrument drift. 6) Sampling error due to the distribution of emission concentrations in space is the single largest source of uncertainty in gas turbine emission measurements.     

Open-path tunable diode laser absorption spectroscopy for acquisition of fugitive emission flux data

Air pollutant emission from unconfined sources is an increasingly important environmental issue. The U.S. Environmental Protection Agency (EPA) has developed a ground-based optical remote-sensing method that enables direct measurement of fugitive emission flux from large area sources. Open-path Fourier transform infrared spectroscopy (OP-FTIR) has been the primary technique for acquisition of pollutant concentration data used in this emission measurement method. For a number of environmentally important compounds, such as ammonia and methane, open-path tunable diode laser absorption spectroscopy (OP-TDLAS) is shown to be a viable alternative to Fourier transform spectroscopy for pollutant concentration measurements. Near-IR diode laser spectroscopy systems offer significant operational and cost advantages over Fourier transform instruments enabling more efficient implementation of the measurement strategy. This article reviews the EPA's fugitive emission measurement method and describes its multipath tunable diode laser instrument. Validation testing of the system is discussed. OP-TDLAS versus OP-FTIR correlation testing results for ammonia (R2 = 0.980) and methane (R2 = 0.991) are reported. Two example applications of tunable diode laser-based fugitive emission measurements are presented.     

Narrow stack emissions: Errors in flow rate measurement due to disturbances and swirl

ABSTRACT

European legislation continues to drive down emission limit values, making the emission measurement of narrow stacks of increasing importance. However, the applicable standards (EN ISO 16911–1 and EN 15259) are poorly validated for narrow stacks, and the effect of flow disturbances on the described methods are largely unknown. In this article, measurement errors are investigated in narrow stacks with flow disturbances and swirl, both experimentally and through computational fluid dynamics (CFD) simulations. The results indicate that measurement errors due to misalignment of the flow with typical measuring probes (pitot tubes) are small compared to errors resulting from the positioning of these probes in the measurement plane. Errors up to 15% are reported using the standardized methods, while the measurement error is both smaller and more predictable when using additional measurement points.

Implications: Current international standards provide methods to measure emissions from industrial stacks. With increasingly small emission limit values, the accuracy of these measurements is becoming considerably more important. The data from this study can be used to inform revisions of these standards, in particular with respect to flow disturbances in narrow stacks, and can help law- and policy-makers to obtain insight into the uncertainties of emission measurements in these specific situations.     

Innovative approach for estimating fugitive gaseous fluxes using computed tomography and remote optical sensing techniques.

This paper presents a new approach to quantify emissions from fugitive gaseous air pollution sources. The authors combine Computed Tomography (CT) with Path-Integrated Optical Remote Sensing (PI-ORS) concentration data in a new field beam geometry. Path-integrated concentrations are sampled in a vertical plane downwind from the source along several radial beam paths. An innovative CT technique, which applies the Smooth Basis Function Minimization method to the beam data in conjunction with measured wind data, is used to estimate the total flux from the fugitive source. The authors conducted a synthetic data study to evaluate the proposed methodology under different meteorological conditions, beam geometry configurations, and simulated measurement errors. The measurement errors were simulated based on data collected with an Open-Path Fourier Transform Infra-Red system. This approach was found to be robust for the simulated errors and for a wide range of fluctuating wind directions. In the very sparse beam geometry examined (eight beam paths), successful emission rates were retrieved over a 70 degrees range of wind directions under extremely large measurement error conditions.     

Systematic error and uncertain carbon dioxide emissions from U.S. power plants

Carbon dioxide (CO₂) emissions from U.S. power plants are independently reported by the U.S. Energy Information Administration (EIA) and the Clean Air Markets Division (CAMD) within the U.S. Environmental Protection Agency (EPA). Differences between the CAMD and EIA emission tallies show that the amount of CO₂ produced by an individual power plant is less certain than might be imagined or desired. These differences are attributed to systematic error and random measurement error. Random error cannot be retroactively corrected, whereas systematic error can be corrected where relevant data are available. Accordingly, this study identified and, where possible, corrected systematic error affecting the CAMD and EIA CO₂ emission tallies for 1065 power plants that emitted more than 25,000 tons of CO₂ during 2013. The EIA tallies were corrected by accounting for emission factor error, acid-gas sorbent consumption, and combustion of biogenic fuel. The CAMD tallies were likewise corrected by accounting for unreported unit emissions. It was not possible to objectively correct systematic error affecting about 11% of the power plants, and subjective corrections were not attempted. At these plants, the CAMD and EIA emission tallies sometimes differed by more than 20% due to missing unit error, plant identification error, temporal measurement error, or inferred reporting error. Comparisons of the CAMD and EIA emission tallies before and after correction for systematic error show the effectiveness of these corrections. The comparisons also show the persistence of random measurement error.

Implications: Understanding the uncertainty of CO2 emission tallies for USA power plants might inform emission inventories, atmospheric flow models or inversions, and emission reduction policies. Knowing the cause and size of measurement errors that contribute to this uncertainty might also help to identify ways to improve the measurement methods and reporting protocols that these CO2 emission tallies are based on.     

Innovative Approach for Estimating Fugitive Gaseous Fluxes Using Computed Tomography and Remote Optical Sensing Techniques

ABSTRACT

This paper presents a new approach to quantify emissions from fugitive gaseous air pollution sources. The authors combine Computed Tomography (CT) with Path-Integrated Optical Remote Sensing (PI-ORS) concentration data in a new field beam geometry. Path-integrated concentrations are sampled in a vertical plane downwind from the source along several radial beam paths. An innovative CT technique, which applies the Smooth Basis Function Minimization method to the beam data in conjunction with measured wind data, is used to estimate the total flux from the fugitive source. The authors conducted a synthetic data study to evaluate the proposed methodology under different meteorological conditions, beam geometry configurations, and simulated measurement errors. The measurement errors were simulated based on data collected with an Open-Path Fourier Transform Infra-Red system. This approach was found to be robust for the simulated errors and for a wide range of fluctuating wind directions. In the very sparse beam geometry examined (eight beam paths), successful emission rates were retrieved over a 70° range of wind directions under extremely large measurement error conditions.     

Validation of the Digital Opacity Compliance System under Regulatory Enforcement Conditions

Abstract

U.S. Environmental Protection Agency (EPA) Emission Measurement Center in conjunction with EPA Regions VI and VIII, the state of Utah, and the U.S. Department of Defense have conducted a series of long-term pilot and field tests to determine the accuracy and reliability of a visible opacity monitoring system consisting of a conventional digital camera and a separate computer software application for plume opacity determination. This technology, known as the Digital Opacity Compliance System (DOCS), has been successfully demonstrated at EPA-sponsored Method-9 “smoke schools,” as well as at a number of government and commercially operated industrial facilities.

Results from the current DOCS regulatory pilot study demonstrated that, under regulatory enforcement conditions, the average difference in opacity measurement between the DOCS technology and EPA Reference Method 9 (Method 9) was 1.12%. This opacity difference, which was computed from the evaluation of 241 regulated air sources, was found to be statistically significant at the 99% confidence level. In evaluating only those sources for which a nonzero visible opacity level was recorded, the average difference in opacity measurement between the DOCS technology and Method 9 was 1.20%. These results suggest that the two opacity measurement methods are essentially equivalent when measuring the opacity of visible emissions.

Given the costs and technical limitations associated with use of Method 9, there is a recognized need to develop accurate, reproducible, and scientifically defensible alternatives to the use of human observers. The use of digital imaging/processing brings current technology to bear on this important regulatory issue. Digital technology offers increased accuracy, a permanent record of measurement events, lower costs, and a scientifically defensible approach for opacity determination.     

Comparison of methods for measurement of cooling tower drift

An international comparison of methods for measurement of cooling tower drift has been performed at the Massachusetts Institute of Technology. Participants from Belgium, the United States and the Federal Republic of Germany participated in measurements of a spectrum of test environments, which span the range of cases which would typically be encountered in operating cooling towers. The environments differed according to droplet mass flux, droplet size distribution and gas speed. A wind tunnel was built to provide the various test environments, and a special optical drift measurement system was built to permit simultaneous monitoring of the environment sampled in the tests. Cases tested included both mechanical and natural draft cooling tower environments.Among the types of instruments tested are the pulsed laser light scattering system (PILLS), sensitive paper and other sensitive surface droplet impaction systems, isokinetic drift mass flux measurement systems and photographic systems. The results indicate that the instruments tested vary widely in their capabilities, with droplet sizing instruments being more effective in low load, small droplet size spectrum situations, and isokinetic mass and chemical assay techniques being most accurate in high load, large droplet distribution cases. Instruments relying upon thermodynamic state measurements in most cases agreed mutually within an order of magnitude. Their major source of error is believed to arise in the measurement of the gas stream relative humidity. This quantity is necessary for inferring the drift mass flux from the measurement provided by such instruments, which is the mixture saturation deficit or excess. For these tests the relative humidity was typically ⩽ 98%.     

Continuous Measurement of Diesel Particulate Emissions

Evaluation of emerging diesel particulate emissions control technology will require analytical procedures capable of continuous or “real-time” measurement of transient organic and elemental carbon emissions. Procedures based on the flame ionlzation properties of organic carbon and the opacity or light extinction properties of elemental carbon are described, and applied for measurement of particulate emissions from diesel engines. The Instrumentation provided adequate sensitivity and time resolution for observation of the transient emissions associated with typical automobile urban driving conditions. Analytical accuracy is evaluated by comparing Integrated average results to measurements using classical gravimetric filtration and solvent extraction procedures. Mass specifc extinction coefficients are evaluated using the Beer-Lambert law. A simplified linear model relating elemental carbon concentration to opacity is also evaluated.     

Bayesian treatment of a chemical mass balance receptor model with multiplicative error structure

The chemical mass balance (CMB) receptor model is commonly used in source apportionment studies as a means for attributing measured airborne particulate matter (PM) to its constituent emission sources. Traditionally, error terms (e.g., measurement and source profile uncertainty) associated with the model have been treated in an additive sense. In this work, however, arguments are made for the assumption of multiplicative errors, and the effects of this assumption are realized in a Bayesian probabilistic formulation which incorporates a ‘modified’ receptor model. One practical, beneficial effect of the multiplicative error assumption is that it automatically precludes the possibility of negative source contributions, without requiring additional constraints on the problem. The present Bayesian treatment further differs from traditional approaches in that the source profiles are inferred alongside the source contributions. Existing knowledge regarding the source profiles is incorporated as prior information to be updated through the Bayesian inferential scheme. Hundreds of parameters are therefore present in the expression for the joint probability of the source contributions and profiles (the posterior probability density function, or PDF), whose domain is explored efficiently using the Hamiltonian Markov chain Monte Carlo method. The overall methodology is evaluated and results compared to the US Environmental Protection Agency's standard CMB model using a test case based on PM data from Fresno, California.     

Calculation of Smoke Plume Opacity from Particulate Air Pollutant Properties

Calculation of smoke plume opacity from the properties of the particulate emission is facilitated with the use of a parameter K (specific particulate volume cm³/m³/extinction coefficient m^?1) computed from theory. Graphs of K vs. the geometric mass mean particle radius at geometric standard deviations from 1 (monodisperse) to 10 are presented for particle refractive indices of 1.96–0.66i (carbon), 2.80–0.02i, 1.33 (water) and 1.50 at a wavelength of light of 550 nm. Experimental data of K for various sources are reported. Application to the estimation of the Ringelmann number is discussed and illustrated with an example.     

Field evaluation of digital optical method to quantify the visual opacity of plumes

Visual Determination of the Opacity of Emissions from Stationary Sources (Method 9) is a reference method established by U.S. Environmental Protection Agency (EPA) to quantify plume opacity. However, Method 9 relies on observations from humans, which introduces subjectivity. In addition, it is expensive to teach and certify personnel to evaluate plume opacity on a semiannual basis. In this study, field tests were completed during a "smoke school" and a 4-month monitoring program of plumes emitted from stationary sources with a Method 9 qualified observer to evaluate the use of digital photography and two computer algorithms as an alternative to Method 9. This Digital Optical Method (DOM) improves objectivity, costs less to implement than Method 9, and provides archival photographic records of the plumes. Results from "smoke school" tests indicate that DOM passed six of eight tests when the sun was located in the 140 degrees sector behind one of the three cameras, with the individual opacity errors of 15% or less and average opacity errors of 7.5% or less. DOM also passed seven of the eight tests when the sun was located in the 216 degrees sector behind another camera. However, DOM passed only one of the eight tests when the sun was located in the 116 degrees sector in front of the third camera. Certification to read plume opacity by a "smoke reader" for 6 months requires that the "smoke reader" pass one of the smoke school tests during smoke school. The average opacity errors and percentage of observations with individual opacity errors above 15% for the results obtained with DOM were lower than those obtained by the smoke school trainees with the sun was located behind the camera, whereas they were higher than the smoke school trainee results with the sun located in front of the camera. In addition, the difference between plume opacity values obtained by DOM and a Method 9 qualified observer, as measured in the field for two industrial sources, were 2.2%. These encouraging results demonstrate that DOM is able to meet Method 9 requirements under a wide variety of field conditions and, therefore, has potential to be used as an alternative to Method 9.     

Emissions from oil and gas operations in the United States and their air quality implications

The energy supply infrastructure in the United States has been changing dramatically over the past decade. Increased production of oil and natural gas, particularly from shale resources using horizontal drilling and hydraulic fracturing, made the United States the world’s largest producer of oil and natural gas in 2014. This review examines air quality impacts, specifically, changes in greenhouse gas, criteria air pollutant, and air toxics emissions from oil and gas production activities that are a result of these changes in energy supplies and use. National emission inventories indicate that volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from oil and gas supply chains in the United States have been increasing significantly, whereas emission inventories for greenhouse gases have seen slight declines over the past decade. These emission inventories are based on counts of equipment and operational activities (activity factors), multiplied by average emission factors, and therefore are subject to uncertainties in these factors. Although uncertainties associated with activity data and missing emission source types can be significant, multiple recent measurement studies indicate that the greatest uncertainties are associated with emission factors. In many source categories, small groups of devices or sites, referred to as super-emitters, contribute a large fraction of emissions. When super-emitters are accounted for, multiple measurement approaches, at multiple scales, produce similar results for estimated emissions. Challenges moving forward include identifying super-emitters and reducing their emission magnitudes. Work done to date suggests that both equipment malfunction and operational practices can be important. Finally, although most of this review focuses on emissions from energy supply infrastructures, the regional air quality implications of some coupled energy production and use scenarios are examined. These case studies suggest that both energy production and use should be considered in assessing air quality implications of changes in energy infrastructures, and that impacts are likely to vary among regions.

Implications: The energy supply infrastructure in the United States has been changing dramatically over the past decade, leading to changes in emissions from oil and natural gas supply chain sources. In many source categories along these supply chains, small groups of devices or sites, referred to as super-emitters, contribute a large fraction of emissions. Effective emission reductions will require technologies for both identifying super-emitters and reducing their emission magnitudes.     

Assessing the uncertainty associated with national greenhouse gas emission inventories:: a case study for Austria

The uncertainty associated with the Austrian Greenhouse Gas emission inventory has been determined for the gases CO₂, CH₄ and N₂O and for the overall greenhouse potential. Expert interviews were conducted to obtain uncertainties in inventory input data. Based on these interviews, error distributions were developed and combined using Monte-Carlo analysis. Results for all sources and gases combined indicate an overall uncertainty between 10.5% and 12% depending on the base year considered. Excluding emissions and the uncertainty associated with forest sinks and natural sources, overall uncertainty decreased by 2% points. The mere ‘random error’, which is considered the level of uncertainty to be achieved with the current methodology (excluding all systematic errors) is 5% points lower. Detailed evaluation shows that much of the overall uncertainty derives from a lack of understanding the processes associated with N₂O emissions from soils. Other important contributors to GHG emission uncertainties are CH₄ from landfills and forests as CO₂ sinks. The uncertainty of the trend has been determined at near 5% points, with solid waste production (landfills) having the strongest contribution. Theoretical considerations do not permit a decrease of the trend uncertainty—even when forest sinks are not considered—below 3% points.     

Nonlinearities in source receptor relationships for sulfur and nitrogen compounds

The relationship between emissions and deposition of air pollutants, both spatially and in time forms an important focus for science and for policy makers. In practice, this relationship may become nonlinear if the underlying processes change with time, or in space. Nonlinearities may also appear due to errors in emission or deposition data, and careful scrutiny of both data sources and their relationship provides a means of picking up such deficiencies. Nonlinearities in source receptor relationships for sulfur and nitrogen compounds in Europe have been identified in measurement data for the UK. In the case of sulfur, the dry deposition process has been shown to be strongly influenced by ambient concentrations of NH3, leading to substantial increases in deposition rate as SO2 concentrations decline and the ratio SO2/NH3 decreases. The field evidence extends to measurements over three different surfaces in three countries across Europe. A mechanistic understanding of the cause of this nonlinearity has been provided. Apparent nonlinearities also exist in the sulfur deposition field through the influence of shipping emissions. The effect is clear at west coast locations, where during a period in which land-based sulfur emissions declined by 50%, no significant decline in concentrations of SO(2-) in precipitation were observed. The sites affected are primarily the coastal regions of southwestern UK, where shipping sources contribute a substantial fraction of the deposited sulfur, but the effect is not detectable elsewhere. Full quantification of the spatially disaggregated emission and their changes in time will eliminate this apparent nonlinearity in the source-receptor data. For oxidized nitrogen emission and deposition in the UK, there is strong evidence of nonlinearity in the source-receptor relationship. The concentrations and deposition of NO(3-) in precipitation have declined little following a reduction in emissions of 45% during the period 1987 to 2001. The data imply a significant decrease in the average transport distance for oxidized nitrogen and most probably an increase in the average oxidation rate. However, the net effect of changes in aerosol chemistry due to changes in sulfur emissions and less competition for the main oxidants as a consequence of reductions in sulfur emission have not been separated. A quantitative explanation of the cause of this nonlinearity is lacking and the effects are therefore identified as an important uncertainty for the development of further protocols to control acidification, eutrophication and photochemical oxidants in Europe.     

Rethinking the assessment of photochemical modelin systems in air quality planning applications

The U.S. Environmental Protection Agency provides guidelines for demonstrating that future 8-hr ozone (O3) design values will be at or below the National Ambient Air Quality Standards on the basis of the application of photochemical modeling systems to simulate the effect of emission reductions. These guidelines also require assessment of the model simulation against observations. In this study, we examined the link between the simulated relative responses to emission reductions and model performance as measured by operational evaluation metrics, a part of the model evaluation required by the guidance, which often is the cornerstone of model evaluation in many practical applications. To this end, summertime O3 concentrations were simulated with two modeling systems for both 2002 and 2009 emission conditions. One of these two modeling systems was applied with two different parameterizations for vertical mixing. Comparison of the simulated base-case 8-hr daily maximum O3 concentrations showed marked model-to-model differences of up to 20 ppb, resulting in significant differences in operational model performance measures. In contrast, only relatively minor differences were detected in the relative response of O3 concentrations to emission reductions, resulting in differences of a few ppb or less in estimated future year design values. These findings imply that operational model evaluation metrics provide little insight into the reliability of the actual model application in the regulatory setting (i.e., the estimation of relative changes). In agreement with the guidance, it is argued that more emphasis should be placed on the diagnostic evaluation of O3-precursor relationships and on the development and application of dynamic and retrospective evaluation approaches in which the response of the model to changes in meteorology and emissions is compared with observed changes. As an example, simulated relative O3 changes between 1995 and 2007 are compared against observed changes. It is suggested that such retrospective studies can serve as the starting point for targeted diagnostic studies in which individual aspects of the modeling system are evaluated and refined to improve the characterization of observed changes.     

Air Levels and Mutagenicity of PM-10 in an Indoor Ice Arena

Abstract

Hazardous waste sites and industrial facilities contain area sources of fugitive emissions. Emission rate measurements or estimates are necessary for air pathway assessments for these sources. Emission rate data can be useful for the design of emission control and remediation strategies as well as for predictive modeling for population exposure assessments. This paper describes the use of a direct emission measurement approach – the enclosure approach using an emission isolation flux chamber – to measure emission rates of various volatile organic compounds (VOCs) from contaminated soil and water. A variety of flux chamber equipment designs and operating procedures have been employed by various researchers. This paper contains a review of the design and operational variables that affect the accuracy and precision of the method. Guidance is given as to the optimum flux chamber design and operating conditions for various types of emission sources. Also presented is a generic quality control program that gives the minimum number of duplicate, blank, background, and repeat samples that should be performed.     

Validation of the digital opacity compliance system under regulatory enforcement conditions

U.S. Environmental Protection Agency (EPA) Emission Measurement Center in conjunction with EPA Regions VI and VIII, the state of Utah, and the U.S. Department of Defense have conducted a series of long-term pilot and field tests to determine the accuracy and reliability of a visible opacity monitoring system consisting of a conventional digital camera and a separate computer software application for plume opacity determination. This technology, known as the Digital Opacity Compliance System (DOCS), has been successfully demonstrated at EPA-sponsored Method-9 "smoke schools", as well as at a number of government and commercially operated industrial facilities. Results from the current DOCS regulatory pilot study demonstrated that, under regulatory enforcement conditions, the average difference in opacity measurement between the DOCS technology and EPA Reference Method 9 (Method 9) was 1.12%. This opacity difference, which was computed from the evaluation of 241 regulated air sources, was found to be statistically significant at the 99% confidence level. In evaluating only those sources for which a nonzero visible opacity level was recorded, the     

Simulation of stack plume opacity

The visual impact of primary particles emitted from stacks is regulated according to stack opacity criteria. In-stack monitoring of the flue gas opacity allows plant operators to ensure that the plant meets U.S. Environmental Protection Agency opacity regulations. However, the emission of condensable gases such as SO3 (that hydrolyzes to H2SO4), HCl, and NH3, which may lead to particle formation after their release from the stack, makes the prediction of stack plume opacity more difficult. We present here a computer simulation model that calculates the opacity due to both primary particles emitted from the stack and secondary particles formed in the atmosphere after the release of condensable gases from the stack. A comprehensive treatment of the plume rise due to buoyancy and momentum is used to calculate the location at which the condensed water plume has evaporated (i.e., where opacity regulations apply). Conversion of H2SO4 to particulate sulfate occurs through nucleation and condensation on primary particles. A thermodynamic aerosol equilibrium model is used to calculate the amount of ammonium, chloride, and water present in the particulate phase with the condensed sulfate. The model calculates the stack plume opacity due to both primary and secondary particles. Examples of model simulations are presented for three scenarios that differ by the emission control equipment installed at the power plant: (1) electrostatic precipitators (ESP), (2) ESP and flue gas desulfurization, and (3) ESP and selective catalytic reduction. The calculated opacity is most sensitive to the primary particulate emissions. For the conditions considered here, SO3 emissions showed only a small effect, except if one assumes that most H2SO4 condenses on primary particles. Condensation of NH4Cl occurs only at high NH3 emission rates (about 25 ppm stack concentration).     

Validating a nondestructive optical method for apportioning colored particulate matter into black carbon and additional components

Exposure of black carbon (BC) is associated with a variety of adverse health outcomes. A number of optical methods for estimating BC on Teflon filters have been adopted but most assume all light absorption is due to BC while other sources of colored particulate matter exist. Recently, a four-wavelength-optical reflectance measurement for distinguishing second hand cigarette smoke (SHS) from soot-BC was developed (Brook et al., 2010; Lawless et al., 2004). However, the method has not been validated for soot-BC nor SHS and little work has been done to look at the methodological issues of the optical reflectance measurements for samples that could have SHS, BC, and other colored particles. We refined this method using a lab-modified integrating sphere with absorption measured continuously from 350 nm to 1000 nm. Furthermore, we characterized the absorption spectrum of additional components of particulate matter (PM) on PM(2.5) filters including ammonium sulfate, hematite, goethite, and magnetite. Finally, we validate this method for BC by comparison to other standard methods. Use of synthesized data indicates that it is important to optimize the choice of wavelengths to minimize computational errors as additional components (more than 2) are added to the apportionment model of colored components. We found that substantial errors are introduced when using 4 wavelengths suggested by Lawless et al. to quantify four substances, while an optimized choice of wavelengths can reduce model-derived error from over 10% to less than 2%. For environmental samples, the method was sensitive for estimating airborne levels of BC and SHS, but not mass loadings of iron oxides and sulfate. Duplicate samples collected in NYC show high reproducibility (points consistent with a 1:1 line, R(2) = 0.95). BC data measured by this method were consistent with those measured by other optical methods, including Aethalometer and Smoke-stain Reflectometer (SSR); although the SSR looses sensitivity at filter loadings above 90 ng/mm(2). Furthermore, positive correlations (R(2) = 0.7) were observed between EC measured by NIOSH Method 5040 on quartz filters and BC measured in co-located Teflon filter samples collected from both heating and non-heating seasons. Overall, the validation data demonstrates the usefulness of this method to evaluate BC from archived Teflon filters while potentially providing additional component information.