Dilution-based emissions sampling from stationary sources: Part 2--Gas-fired combustors compared with other fuel-fired systems

With the recent focus on fine particle matter (PM2.5), new, self-consistent data are needed to characterize emissions from combustion sources. Such data are necessary for health assessment and air quality modeling. To address this need, emissions data for gas-fired combustors are presented here, using dilution sampling as the reference. The dilution method allows for collection of emitted particles under conditions simulating cooling and dilution during entry from the stack into the air. The sampling and analysis of the collected particles in the presence of precursor gases, SO2 nitrogen oxide, volatile organic compound, and NH3 is discussed; the results include data from eight gas fired units, including a dual-fuel institutional boiler and a diesel engine powered electricity generator. These data are compared with results in the literature for heavy-duty diesel vehicles and stationary sources using coal or wood as fuels. The results show that the gas-fired combustors have very low PM2.5 mass emission rates in the range of approximately 10(-4) lb/million Btu (MMBTU) compared with the diesel backup generator with particle filter, with approximately 5 x 10(-3) lb/MMBTU. Even higher mass emission rates are found in coal-fired systems, with rates of approximately 0.07 lb/MMBTU for a bag-filter-controlled pilot unit burning eastern bituminous coal. The characterization of PM2.5 chemical composition from the gas-fired units indicates that much of the measured primary particle mass in PM2.5 samples is organic or elemental carbon and, to a much less extent, sulfate. Metal emissions are quite low compared with the diesel engines and the coal- or wood-fueled combustors. The metals found in the gas-fired combustor particles are low in concentration, similar in concentration to ambient particles. The interpretation of the particulate carbon emissions is complicated by the fact that an approximately equal amount of particulate carbon (mainly organic carbon) is found on the particle collector and a backup filter. It is likely that measurement artifacts, mostly adsorption of volatile organic compounds on quartz filters, are positively biasing "true" particulate carbon emission results.     

Design of a compact dilution sampler for stationary combustion sources

The dilution sampling method simulates the rapid cooling and dilution processes after hot flue gas have left the stack. This allows gases or vapors to nucleate both homogeneously and heterogeneously, and to condense on preexisting particles in processes analogous to those that occur in the ambient environment. Using this method the authors can collect filterable particulate matter (PM) and condensible PM, that is, primary PM, simultaneously. In order to make this method more suitable for field investigation, a compact dilution sampler was developed. The sampler enhances mixing of dilution air with the stack gas, and thus shortens the length of the mixing section. The design decreases the nominal flow rate through the aging section, and accordingly reduces the size of the residence chamber. The decreased size of the sampler is suitable for field test. Sampling gas is pressured into the residence chamber, and air pressure in the chamber is micro-positive. Uncollected redundant gas is automatically discharged through unused sampling ports, which keeps the unit stable. Performance evaluation tests demonstrate that the design is reasonable. The sampler has been applied to characterize PM emissions from various combustion sources in China.     

Estimation of Organic Compound Emissions from Waste Lagoons

Abstract

With the recent focus on fine particle matter (PM_2.5),new, self-consistent data are needed to characterize emissions from combustion sources. Such data are necessary for health assessment and air quality modeling. To address this need, emissions data for gas-fired combustors are presented here, using dilution sampling as the reference.The dilution method allows for collection of emitted particles under conditions simulating cooling and dilution during entry from the stack into the air. The sampling and analysis of the collected particles in the presence of precursor gases, SO₂, nitrogen oxide, volatile organic compound, and NH₃ is discussed; the results include data from eight gas fired units, including a dual-fuel institutional boiler and a diesel engine powered electricity generator. These data are compared with results in the literature for heavy-duty diesel vehicles and stationary sources using coal or wood as fuels. The results show that the gas-fired combustors have very low PM_2.5 mass emission rates in the range of ～10_-4 lb/million Btu (MMBTU) compared with the diesel backup generator with particle filter, with ～5 × 10_-3 lb/MMBTU. Even higher mass emission rates are found in coal-fired systems, with rates of ～0.07 lb/MMBTU for a bag-filter-controlled pilot unit burning eastern bituminous coal. The characterization of PM_2.5 chemical composition from the gas-fired units indicates that much of the measured primary particle mass in PM_2.5 samples is organic or elemental carbon and, to a much less extent, sulfate. Metal emissions are quite low compared with the diesel engines and the coal- or woodfueled combustors. The metals found in the gas-fired combustor particles are low in concentration, similar in concentration to ambient particles. The interpretation of the particulate carbon emissions is complicated by the fact that an approximately equal amount of particulate carbon (mainly organic carbon) is found on the particle collector and a backup filter. It is likely that measurement artifacts, mostly adsorption of volatile organic compounds on quartz filters, are positively biasing “true” particulate carbon emission results.     

Woodstove smoke and CO emissions: comparison of reference methods with the VIP sampler

A new field sampler has been developed for measuring the particulate matter (PM) and carbon monoxide emissions of woodburning stoves. Particulate matter is determined by carbon balance and the workup of a sample train which is similar to a room-temperature EPA Method 5G train. A steel tank, initially evacuated, serves as the motive force for sampling and also accumulates a gas sample for post-test analysis of time-averaged stack CO and CO2 concentrations. Workup procedures can be completed within 72 hours of sampler retrieval. The system has been compared to reference methods in two laboratory test series involving six different woodburning appliances and two independent laboratories. The correlation of field sampler emission rates and reference method rates is strong.     

Woodstove Smoke and CO Emissions: Comparison of Reference Methods with the VPI Sampler

A new field sampler has been developed for measuring the particulate matter (PM) and carbon monoxide emissions of woodburning stoves. Particulate matter is determined by carbon balance and the workup of a sample train which is similar to a room-temperature EPA Method 5G train. A steel tank, initially evacuated, serves as the motive force for sampling and also accumulates a gas sample for post-test analysis of time-averaged stack CO and CO₂ concentrations. Workup procedures can be completed, within 72 hours of sampler retrieval. The system has been compared to reference methods in two laboratory test series involving six different woodburning appliances and two independent laboratories. The correlation of field sampler emission rates and reference method rates is strong.     

Hot filter/impinger and dilution sampling for fine particulate matter characterization from ferrous metal casting processes

A study using two stack-sampling methodologies for collecting particulate matter (PM) emissions was conducted using a hot filter followed by a cold impinger sampling train and a dilution sampler. Samples were collected from ferrous iron metal casting processes that included pouring molten iron into a sand mold containing an organic binder, metal cooling, removal of the sand from the cooled casting (shakeout), and postshakeout cooling. The shakeout process contributed more to PM emissions than the metal pouring and cooling processes. Particulate matter less than 2.5 microm in aerodynamic diameter (PM2.5) mass emissions for the entire casting cycle ranged from 3.4 to 4.7 lb/t of metal for the hot filter/impinger method and from 0.8 to 1.8 lb/t of metal for the dilution method. Most of the difference was due to PM captured by the impingers, much of which was probably dissolved gases rather than condensable vapors. Of the PM fraction captured by the impingers, 96-98% was organic in nature. The impinger PM fraction contributed 32-38% to the total suspended particle mass and caused a factor of 2-4 positive bias for PM2.5 emissions. For the pouring and cooling processes only, the factor increased to over seven times.     

Hot Filter/Impinger and Dilution Sampling for Fine Particulate Matter Characterization from Ferrous Metal Casting Processes

Abstract

A study using two stack-sampling methodologies for collecting particulate matter (PM) emissions was conducted using a hot filter followed by a cold impinger sampling train and a dilution sampler. Samples were collected from ferrous iron metal casting processes that included pouring molten iron into a sand mold containing an organic binder, metal cooling, removal of the sand from the cooled casting (shakeout), and postshakeout cooling. The shakeout process contributed more to PM emissions than the metal pouring and cooling processes. Particulate matter less than 2.5 μm in aerodynamic diameter (PM_2.5) mass emissions for the entire casting cycle ranged from 3.4 to 4.7 lb/t of metal for the hot filter/impinger method and from 0.8 to 1.8 lb/t of metal for the dilution method. Most of the difference was due to PM captured by the impingers, much of which was probably dissolved gases rather than condensable vapors. Of the PM fraction captured by the impingers, 96–98% was organic in nature. The impinger PM fraction contributed 32–38% to the total suspended particle mass and caused a factor of 2–4 positive bias for PM_2.5 emissions. For the pouring and cooling processes only, the factor increased to over seven times.     

In-stack condensible particulate matter measurements and issues

Particulate matter (PM) emitted from fossil fuel-fired units can be classified as either filterable or condensible PM. Condensible PM typically is not measured because federal and most state regulations do not require sources to do so. To determine the magnitude of condensible PM emissions relative to filterable PM emissions and to better understand condensible PM measurement issues, a review and analysis of actual U.S. Environmental Protection Agency (EPA) Method 202 (for in-stack condensible PM10) and EPA Method 201/201A (for in-stack filterable PM10) results were conducted. Methods 202 and 201/201A results for several coal-burning boilers showed that the condensible PM, on average, comprises approximately three-fourths (76%) of the total PM10 stack emissions. Methods 202 and 201/201A results for oil- and natural gas-fired boilers showed that the condensible PM, on average, comprises 50% of the total PM10 stack emissions. Methods 202 and 201/201A results for oil-, natural gas-, and kerosene-fired combustion turbines showed that the condensible PM, on average, comprises 69% of the total PM10 stack emissions. Based on these limited measurements, condensible PM can make a significant contribution to total PM10 emissions for fossil fuel-fired units. A positive bias (indicating more condensible PM than is actually emitted) may exist in the measured data due to the conversion of dissolved sulfur dioxide to sulfate compounds in the sampling procedure. In addition, these Method 202 results confirm that condensible PM, on average, is composed mostly of inorganic matter, regardless of the type of fuel burned.     

Current status of air quality models for particulate matter.

The current status of the mathematical modeling of atmospheric particulate matter (PM) is reviewed in this paper. Simulating PM requires treating various processes, including the formation of condensable species, the gas/ particle partitioning of condensable compounds, and in some cases, the evolution of the particle size distribution. The algorithms available to simulate these processes are reviewed and discussed. Eleven 3-dimensional (3-D) Eulerian air quality models for PM are reviewed in terms of their formulation and past applications. Results of past performance evaluations of 3-D Eulerian PM models are presented. Currently, 24-hr average PM2.5 concentrations appear to be predicted within 50% for urban-scale domains. However, there are compensating errors among individual particulate species. The lowest errors tend to be associated with SO4(2-), while NO3-, black carbon (BC), and organic carbon (OC) typically show larger errors due to uncertainties in emissions inventories and the prediction of the secondary OC fraction. Further improvements and performance evaluations are recommended.     

The measurement of fine particulate semivolatile material in urban aerosols

Ammonium nitrate and semivolatile organic material (SVOM) are significant components of fine particles in urban atmospheres. These components, however, are not properly determined with methods such as the fine particulate matter (PM2.5) Federal Reference Method (FRM) or other single filter samplers because of significant losses of semivolatile material (SVM) from particles collected on the filter during sampling. The R&P tapered element oscillating microbalance (TEOM) monitor also does not measure SVM, because this method heats the sample to remove particle bound water, which also results in evaporation of SVM. Recent advances in monitoring techniques have resulted in samplers for both integrated and continuous measurement of total PM2.5, including the particle concentrator-Brigham Young University organic sampling system (PC-BOSS), the real-time total ambient mass sampler (RAMS), and the R&P filter dynamics measurement system (FDMS) TEOM monitor. Results obtained using these samplers have been compared with those obtained with either a PM2.5 FRM sampler or a TEOM monitor in studies conducted during the past five years. These studies have shown the following: (1) the PC-BOSS, RAMS, and FDMS TEOM are all comparable. Each instrument measures both the nonvolatile material and the SVM. (2) The SVM is not retained on the heated filter of a regular TEOM monitor and is not measured by this sampling technique. (3) Much of the SVM is also lost during sampling from single filter samplers such as the PM2.5 FRM sampler. (4) The amount of SVM lost from single filter samplers can vary from less than one-third of that lost from heated TEOM filters during cold winter conditions to essentially all during warm summer conditions. (5) SVOM can only be reliably collected using an appropriate denuder sampler. (6) A PM2.5 speciation sampler can be easily modified to a denuder sampler with filters that can be analyzed for semivolatile organic carbon (OC), nonvolatile OC, and elemental carbon using existing OC/elemental carbon analytical techniques. The research upon which these statements are based for various urban studies are summarized in this paper.     

Continuous determination of fine particulate matter mass in the Salt Lake City Environmental Monitoring project: a comparison of real-time and conventional TEOM monitor results

Fine particulate matter (PM2.5) mass was determined on a continuous basis at the Salt Lake City Environmental Protection Agency Environmental Monitoring for Public Awareness and Community Tracking monitoring site in Salt Lake City, UT, using three different monitoring techniques. Hourly averaged PM2.5 mass data were collected during two sampling periods (summer 2000 and winter 2002) using a real-time total ambient mass sampler (RAMS), sample equilibration system (SES)-tapered element oscillating microbalance (TEOM), and conventional TEOM monitor. This paper compares the results obtained from the various monitoring systems, which differ in their treatment of semivolatile material (SVM; particle-bound water, semivolatile ammonium nitrate, and semivolatile organic compounds). PM2.5 mass results obtained by the RAMS were consistently higher than those obtained by the SES-TEOM and conventional TEOM monitors because of the RAMS ability to measure semivolatile ammonium nitrate and semivolatile organic material but not particle-bound water. The SES-TEOM monitoring system was able to account for an average of 28% of the SVM, whereas the conventional TEOM monitor loses essentially all of the SVM from the single filter during sampling. Occasional mass readings by the various TEOM monitors that are higher than RAMS results may reflect particle-bound water, which, under some conditions, is measured by the TEOM but not the RAMS.     

Current Status of Air Quality Models for Particulate Matter

ABSTRACT

The current status of the mathematical modeling of atmospheric particulate matter (PM) is reviewed in this paper. Simulating PM requires treating various processes, including the formation of condensable species, the gas/ particle partitioning of condensable compounds, and in some cases, the evolution of the particle size distribution. The algorithms available to simulate these processes are reviewed and discussed. Eleven 3-dimensional (3-D) Eulerian air quality models for PM are reviewed in terms of their formulation and past applications. Results of past performance evaluations of 3-D Eulerian PM models are presented. Currently, 24-hr average PM_2.5 concentrations appear to be predicted within 50% for urban-scale domains. However, there are compensating errors among individual particulate species. The lowest errors tend to be associated with SO₄ ^2-, while NO₃ ^-, black carbon (BC), and organic carbon (OC) typically show larger errors due to uncertainties in emissions inventories and the prediction of the secondary OC fraction. Further improvements and performance evaluations are recommended.     

Comparison of speciation sampler and PC-BOSS fine particulate matter organic material results obtained in Lindon, Utah, during winter 2001-2002

The Particle Concentrator-Brigham Young University Organic Sampling System (PC-BOSS) has been previously verified as being capable of measuring total fine particulate matter (PM2.5), including semi-volatile species. The present study was conducted to determine if the simple modification of a commercial speciation sampler with a charcoal denuder followed by a filter pack containing a quartz filter and a charcoal-impregnated glass (CIG) fiber filter would allow for the measurement of total PM2.5, including semi-volatile organic material. Data were collected using an R&P (Rupprecht and Pastasnik Co., Inc.) Partisol Model 2300 speciation sampler; an R&P Partisol speciation sampler modified with a BOSS denuder, followed by a filter pack with a quartz and a CIG filter; a Met One spiral aerosol speciation sampler (SASS); and the PC-BOSS from November 2001 to March 2002 at a U.S. Environmental Protection Agency (EPA) Science to Achieve Results (STAR) sampling site in Lindon, UT. Total PM2.5 mass, ammonium nitrate (both nonvolatile and semi-volatile), ammonium sulfate, organic carbon (both non-volatile and semi-volatile), and elemental carbon were determined on a 24-hr basis. Results obtained with the individual samplers were compared to determine the capability of the modified R&P speciation sampler for measuring total PM2.5, including semi-volatile components. Data obtained with the modified speciation sampler agreed with the PC-BOSS results. Data obtained with the two unmodified speciation samplers were low by an average of 26% because of the loss of semi-volatile organic material from the quartz filter during sample collection.     

Field evaluation of particulate matter measurements using tapered element oscillating microbalance in a layer house

The tapered element oscillating microbalance (TEOM) is one type of continuous ambient particulate matter (PM) monitor. Adsorption and desorption of moisture and semivolatile species may cause positive or negative artifacts in TEOM PM mass measurement. The objective of this field study was to investigate possible uncertainties associated with TEOM measurements in the poultry operation environment. For comparisons of TEOM with filter-based gravimetric method, four instruments (TEOM-PM10, low-volume PM10 sampler TEOM-PM2.5, and PM2.5 speciation sampler) were collocated and tested inside a poultry house for PM2.5 and PM10 (PM with aerodynamic equivalent diameter < or =2.5 and < or =10 microm, respectively) measurements. Fifteen sets of 24-hr PM10 concentrations and 13 sets of 24-hr PM2.5 measurements were obtained. Results indicate that compared with filter-based gravimetric method, TEOM gave significantly lower values of both PM10 and PM2.5 mass concentrations. For PM10, the average ratio of TEOM to the gravimetric method was 0.936. For PM2.5, the average ratio of TEOM to the gravimetric method was 0.738. Particulate matter in the poultry houses possibly contains semivolatile compounds and moisture due to high levels of relative humidity (RH) and gas pollutants. The internal heating mechanism of the TEOM may cause losses in mass through volatilization. To investigate the effects of TEOM settings on concentration measurements, the heaters of two identical TEOMs were set at 50 degrees C, 30 degrees C, or no heating at all. They were collocated and tested for total suspended particle (TSP), PM10, and PM25 measurements in layer house for 6 weeks. For all TSR PM10, and PM2.5 measurements, the internal TEOM temperature setting had a significant effect (P < 0.05). Significantly higher PM mass concentrations were measured at lower temperature settings. The effects of environmental (i.e., temperature, RH, NH3 and CO2 concentrations) and instrumental (i.e., filter loading and noise) parameters on PM measurements were also assessed using regression analysis.     

Apportionment of ambient primary and secondary fine particulate matter at the Pittsburgh National Energy Laboratory particulate matter characterization site using positive matrix factorization and a potential source contributions function analysis

Fine particulate matter (PM2.5) concentrations associated with 202 24-hr samples collected at the National Energy Technology Laboratory (NETL) particulate matter (PM) characterization site in south Pittsburgh from October 1999 through September 2001 were used to apportion PM2.5 into primary and secondary contributions using Positive Matrix Factorization (PMF2). Input included the concentrations of PM2.5 mass determined with a Federal Reference Method (FRM) sampler, semi-volatile PM2.5 organic material, elemental carbon (EC), and trace element components of PM2.5. A total of 11 factors were identified. The results of potential source contributions function (PSCF) analysis using PMF2 factors and HYSPLIT-calculated back-trajectories were used to identify those factors associated with specific meteorological transport conditions. The 11 factors were identified as being associated with emissions from various specific regions and facilities including crustal material, gasoline combustion, diesel combustion, and three nearby sources high in trace metals. Three sources associated with transport from coal-fired power plants to the southeast, a combination of point sources to the northwest, and a steel mill and associated sources to the west were identified. In addition, two secondary-material-dominated sources were identified, one was associated with secondary products of local emissions and one was dominated by secondary ammonium sulfate transported to the NETL site from the west and southwest. Of these 11 factors, the four largest contributors to PM2.5 were the secondary transported material (dominated by ammonium sulfate) (47%), local secondary material (19%), diesel combustion emissions (10%), and gasoline combustion emissions (8%). The other seven factors accounted for the remaining 16% of the PM2.5 mass. The findings are consistent with the major source of PM2.5 in the Pittsburgh area being dominated by ammonium sulfate from distant transport and so decoupled from local activity emitting organic pollutants in the metropolitan area. In contrast, the major local secondary sources are dominated by organic material.     

Theoretical study of the impact of particulate matter gravitational settling on ambient coarse particulate matter monitoring for agricultural emissions

The particle size distributions (PSDs) of particulate matter (PM) in the downwind plume from simulated sources of a cotton gin were analyzed to determine the impact of PM settling on PM monitoring. The PSD of PM in a plume varies as a function of gravitational settling. Gravitational settling has a greater impact on the downwind PSD from sources with PSDs having larger mass median diameters (MMDs). The change in PSD is a function of the source PSD of emitted PM, wind speed, and downwind distance. Both MMD and geometric standard deviation (GSD) in the downwind plume decrease with an increase in downwind distance and source MMD. The larger the source MMD, the greater the change in the downwind MMD and GSD. Also, the greater the distance from the source to the sampler, the greater the change in the downwind MMD and GSD. Variations of the PSD in the downwind plume significantly impact PM10 sampling errors associated with the U.S. Environmental Protection Agency (EPA) PM10 samplers. For the emission sources with MMD > 10 microm, the PM10 oversampling rate increases with an increase in downwind distance caused by the decrease of GSD of the PSD in the downwind plume. Gravitational settling of particles does not help reduce the oversampling problems associated with the EPA PM10 sampler. Furthermore, oversampling rates decrease with an increase of the wind speed.     

Characterization of the fugitive particulate emissions from construction mud/dirt carryout

Although the fugitive dust associated with construction mud/dirt carryout can represent a substantial portion of the particulate matter (PM) emissions inventory in nonattainment areas, it has not been well characterized by direct sampling methods. In this paper, a research program is described that directly determined both PM10 and PM2.5 (particles < or =10 and 2.5 microm in classical aerodynamic diameter, respectively) emission factors for mud/dirt carryout from a major construction project located in metropolitan Kansas City, MO. The program also assessed the contribution of automotive emissions to the total PM2.5 burden and determined the baseline emissions from the test road. As part of the study, both time-integrated and continuous exposure-profiling methods were used to assess the PM emissions, including particle size and elemental composition. This research resulted in overall PM10 and PM2.5 emission factors of 6 and 0.2 g/vehicle, respectively. Although PM10 is within the range of prior U.S. Environmental Protection Agency (EPA) guidance, the PM2.5 emission factor is far lower than previous estimates published by EPA. In addition, based on both the particle size and chemical data obtained in the study, a major portion of the PM2.5 emissions appears to be attributable to automotive exhaust from light-duty, gasoline-powered vehicles and not to the fugitive dust associated with reentrained mud/dirt carryout.     

A constant-volume rapid exhaust dilution system for motor vehicle particulate matter number and mass measurements

An improved version of the constant volume sampling (CVS) methodology that overcomes a number of obstacles that exist with the current CVS dilution tunnel system used in most diesel and gasoline vehicle emissions test facilities is presented. The key feature of the new sampling system is the introduction of dilution air immediately at the vehicle tailpipe. In the present implementation, this is done concentrically through a cylindrical air filter. Elimination of the transfer hose conventionally used to connect the tailpipe to the dilution tunnel significantly reduces the hydrocarbon and particulate matter (PM) storage release artifacts that can lead to wildly incorrect particle number counts and to erroneous filter-collected PM mass. It provides accurate representations of particle size distributions for diesel vehicles by avoiding the particle coagulation that occurs in the transfer hose. Furthermore, it removes the variable delay time that otherwise exists between the time that emissions exit the tailpipe and when they are detected in the dilution tunnel. The performance of the improved CVS system is examined with respect to diesel, gasoline, and compressed natural gas vehicles.     

Demolition of high-rise public housing increases particulate matter air pollution in communities of high-risk asthmatics

Public housing developments across the United States are being demolished, potentially increasing local concentrations of particulate matter (PM) in communities with high burdens of severe asthma. Little is known about the impact of demolition on local air quality. At three public housing developments in Chicago, IL, PM with an aerodynamic diameter < 10 microm (PM10) and < 2.5 microm were measured before and during high-rise demolition. Additionally, size-selective sampling and real-time monitoring were concurrently performed upwind and downwind of one demolition site. The concentration of particulates attributable to demolition was estimated after accounting for background urban air pollution. Particle microscopy was performed on a small number of samples. Substantial increases of PM10 occurred during demolition, with the magnitude of that increase varying based on sampler distance, wind direction, and averaging time. During structural demolition, local concentrations of PM10 42 m downwind of a demolition site increased 4- to 9-fold above upwind concentrations (6-hr averaging time). After adjusting for background PM10, the presence of dusty conditions was associated with a 74% increase in PM10 100 m downwind of demolition sites (24-hr averaging times). During structural demolition, short-term peaks in real-time PM10 (30-sec averaging time) occasionally exceeded 500 microg/m(3). The median particle size downwind of a demolition site (17.3 microm) was significantly larger than background (3 microm). Specific activities are associated with realtime particulate measures. Microscopy did not identify asbestos or high concentrations of mold spores. In conclusion, individuals living near sites of public housing demolition are at risk for exposure to high particulate concentrations. This increase is characterized by relatively large particles and high short-term peaks in PM concentration.     

Transient puffs of trace organic emissions from a batch-fed waste propellant incinerator

Emissions data have been obtained from a waste propellant incinerator. The incinerator is a dual fixed hearth, controlled air incinerator equipped with acid gas and particulate scrubbing. "Puffing" has been evident in this waste propellant incinerator by spikes in the CO concentration. Transient puffs of organics may travel down the combustion chambers and lead to stack emissions. The major conclusions from this study are that (1) transient puffs are formed due to the semi-batch feed nature of the combustion process (causing a local oxygen deficiency) and high water content of the desensitized propellant; (2) in batch-fed combustors, puffs can contribute to most of the organic emissions (which are relatively low) measured with US EPA sampling and analytical methods; (3) it is estimated that batch-fed combustion contributes up to 7-18 times more emissions than steady-state combustion will generate; (4) by applying dispersion analyses to determine the amount of oxygen deficiency in the flame zone, the combustion zone concentration of CO during batch-fed operation could be as high as 160,000 ppm, compared to a measured peak stack concentration of 1200 ppm CO; and (5) an organic sample is collected and averaged over at least a 2-h period that smooths out the transient peaks of organics emissions during batch-fed operation. For emissions that are associated with long-term potential health impacts, this is an appropriate sampling method. However, if a compound has a short-term potential health impact, it may be important to measure the time-resolved emissions of the compound.