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Emissions Monitoring and Analyses for a Micropowdered Biomass Combustor


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The following paper discusses the emissions monitoring system to be applied to a solid biomass burner. Discussion includes description of the experimental apparatus, description and justification of pollutants to be monitored, and collection and analysis techniques for those pollutants. Preliminary experimental data is presented. Introduction This report describes an experimental biomass burner and the emissions sampling system to which it will be attached. Included are specific descriptions of the equipment to be used including operational principles and the specific components of the exhaust which each device will measure. This report is intended as a guideline for constructing an actual emissions monitoring system and the necessary techniques to extract useful data.
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Emissions Monitoring and Analyses for a Micropowdered Biomass Combustor
Mark Fuller, Cornell University
MAE 6480: Air Quality and Atmospheric Chemistry
Professor Max Zhang
Fall 2010
The following paper discusses the emissions monitoring system to be applied to a solid biomass
burner. Discussion includes description of the experimental apparatus, description and
justification of pollutants to be monitored, and collection and analysis techniques for those
pollutants. Preliminary experimental data is presented.
This report describes an experimental biomass burner and the emissions sampling system to
which it will be attached. Included are specific descriptions of the equipment to be used
including operational principles and the specific components of the exhaust which each device
will measure. This report is intended as a guideline for constructing an actual emissions
monitoring system and the necessary techniques to extract useful data.
Burner Apparatus
The burner system used in these experiments is a continuous-feed, laboratory-scale, open-flame
burner, schematically depicted in figure 1.
Fig. 1: Burner system schematic1
The burner fuel is wood powder, with a particle size of approximately 100 microns. Fuel and air
consumption can vary over up to four orders of magnitude based on the experiments being
performed and the exact experimental apparatus being tested. This imposes a requirement on the
emissions monitoring system that it be capable of similar breadth of operation.
Emissions Collection Experimental Apparatus
Sampling of the emissions may be from the exhaust plume above the burner where concentration
and temperatures are low enough for direct sampling or a portion of the exhaust plume may be
directed into a dilution tunnel for mixing with cool, clean air to quench the sample and make it
possible to measure the exhaust before significant particle and chemical reactions have occurred.
Given the relatively small scale of the laboratory burner and a desire to control costs, the dilution
tunnel design we selected for this project was the portable dilution tunnel (PDT) constructed at
Carnegie Mellon University. Figure 2, below, is a schematic of their system, reproduced from
the paper describing the PDT2.
Fig. 2: Schematic of the Carnegie Mellon PDT System
The PDT has seven sampling ports, allowing for the connection of multiple instruments and
simultaneous sampling. The PDT is the simplest component of the emissions system and is
shown in figure 3. Some important aspects of the dilution tunnel for practical application are
that the exhaust inlet line must be heated and that the dilution air must be clean (passed through
HEPA and activated carbon filters). On the sampling end, the cyclone and filter packs can be
used to remove particulates ahead of sensitive, gas-sampling devices which cannot accept
particulates and the filters may also be used to collect particulates for massing and chemical
Fig. 3: PDT, 4.5 inch outside diameter, sampling ports left
Pollutants of Interest
To determine what equipment is needed to complete the emissions system, it must be determined
what components are to be measured. For a typical complete combustion process of a
hydrocarbon fuel, the products are water and carbon dioxide. When this process does not go to
full completion, carbon monoxide is also commonly found. Dissociation of products due to
equilibrium at high temperatures also produces radicals, such as single hydrogen atoms and the
hydroxyl radical (OH). Additionally, due to their environmental implications in ozone formation
3 and acid rain4, respectively, nitrous and sulfuric oxides are of interest. It can be expected that
nitrous oxides will be produced by reactions of atmospheric oxygen and nitrogen at the elevated
temperatures resulting from combustion. Production of some sulfuric oxides can also been
anticipated as wood powder contains approximately 0.01% sulfur by weight5.
Some level of particulate emissions is to be expected. Reported values of the inorganic ash
content of wood, a minimum indicator of expected particulates, varies from 0.4% mass for
spruce wood powder5 up to 2.7% mass for an average of hardwood powders6. For particulate
emissions, mass and size distributions combined with chemical analysis of samples collected on
filters are desired to compare the burner to current standards for air quality. Specific classes of
particulate pollutants to be measured are volatile organic compounds (VOC), polycyclic aromatic
hydrocarbons (PAH), elemental carbon (EC) and organic carbon (OC). VOC contribute to ozone
production3 and PAH, produced by incomplete combustion, and are carcinogenic and pose health
risks7,8. OC can be the result of VOC oxidation (secondary OC) or it may be directly emitted
from the combustion process (primary OC). OC covers a broad class of carbon-containing
particulate emissions. EC is emitted during combustion and is predominantly carbon particles
with some impurities, e.g. C8H8. Knowledge of these values in the emissions can be used to
make corrections (if necessary) in emissions factor calculations carried out by carbon balance9.
The complete list of required measurements for this project, as defined jointly with the New York
State Energy Research Development Authority (NYSERDA): CO, CO2, NOx, SOx, PAH, VOC,
EC, OC, PM2.5, and Particle Size Distribution10.
Measurement Devices
Having established the constituents of the emissions to be measured, we are left to determine
appropriate devices for measuring each. This decision will be based both on resolution and cost
the instruments presently available for our laboratory work will be considered first and
additional devices or components will only be considered where current tools are inadequate.
A literature search into emissions measurement techniques has indicated that Fourier Transform
Infrared Spectrometry (FTIR) may be used to determine the content of CO, CO2, SO211 and also
NO, NO212, satisfying the requirements to monitor CO, CO2, NOx and SOx. For additional
ambient monitoring of CO and CO2, available to us is a hand-held monitor that also collects
temperature and relative humidity13.
Gas Chromatograph - Mass Spectrometry (GC/MS) analysis of samples may also be used to
determine PAH, EC, OC14 and VOC15 content. To measure particle counts and masses, both
distributions and specific values, such as PM2.5, a (portable) aerosol spectrometer (PAS)16,
aerodynamic particle sizer (APS)17 and/or fast-mobility particle sizer (FMPS)18 may be
For measurements in the field and ambient sampling, we have used a combination of a hand-held
CO, CO2 monitor and a portable aerosol spectrometer to determine emission factors (mass of
particulates emitted per unit mass or unit energy of fuel). Our selections for gas analysis, FTIR
and GC/MS, are not portable. This difficulty has been addressed by several researchers, Tami
Bond19, for example. Further, devices designed for specific gas monitoring, such as the hand-
held sensor, do exist for measuring most of the exhaust gases of interest and are sufficiently
accurate to produce publishable data20.
Theories of Operation of Measurement Devices
FTIR: FTIR analysis is a form of absorption spectroscopy. This technique measures reduction
in beam intensity to allow computation of a species partial pressure from a known absorption
coefficient, per Beer's Law
I = Io*exp(-αi*Pi*L)
where I is the measured intensity, Io is the initial intensity, αi is the species adsorption coefficient,
Pi is the species partial pressure, and L is the sample thickness21. Full FTIR analysis relies on the
collection of multiple data points of absorption behavior, each indicative of a different set of
frequencies of light. These various sets of frequencies are produced by using a light source
containing all the desired frequencies of light and then selecting the desired frequencies through
use of a Michelson Inferometer. The accumulated data is eventually processed by means of
Fourier transform to give absorption as a function of wavelength. The Michelson Inferometer
takes a single beam of radiation to a beamsplitter where it is partially transmitted to a moving
mirror and partially reflected to a fixed mirror. The beams return from the mirrors to the
beamsplitter and there interfere before being partly transmitted and partly reflected back to the
source and to a detector22.
Fig. 4: Schematic of Michelson Inferometer23
Fig. 5: Thermo Scientific FT-IR. Samples are contained in the glass chamber.
GC: GC analysis can be used to separate components of a gaseous mixture. Separation is
accomplished by passing a sample through a tube containing an adsorbent. Different gases will
have different characteristics and will consequently pass through the tube at different rates,
leading to an output of peaks when measured against time. The integral of the peak indicates the
amount of the species in the sample and the relative position of the peak indicates the species.
Different columns (adsorbent-lined tubes) are available for different applications21. Separation of
a sample by GC analysis is thus dependent on having some idea ahead of time as to what the
components of the sample will be and selection of an appropriate column.
MS: MS analysis is used to further separate species based on their atomic masses. The species
are bombarded with electrons to form all possible positive ions. Several techniques are used to
separate the ions by mass-to-charge so as to determine the composition of the sample. High
resolution is required for differentiating between species of interest as the atomic mass of N2 is
28.0134 and CO is 28.01 a required resolution of 1e-4. Magnetic deflection mass
spectrometry, the original technique, used crossed magnetic and electric fields to deflect ions.
Variation of either field or the collector position is used to establish the mass-to-charge ratio.
Another technique is time-of-flight mass spectrometry, which uses a pulse of ionization of
several hundred nanoseconds to impart energy to the molecules proportionate to their charge.
Particles reach terminal velocity before impacting on a detector. As the terminal velocity is
affected by mass, each species will arrive at the detector at a different time, proportional to the
square root of the mass. A third type of device is the quadrupole mass spectrometer. Ions are
passed parallel down the center of four electric fields, which may be AC or Dcand of variable
strength and frequency21. The selection of the fields, whether AC or DC and frequency cause
instabilities in the ion trajectories for all but a single mass-to-charge ratio, which may pass to the
detector. This list of MS techniques is not exhaustive. The collected data is in the form of a
distribution of ion flux as a function of mass-to-charge ratio. This is compared to a data library
to determine the composition of the original sample21.
Fig. 6: GC-MS Assembly: Thermo Scientific Trace GC Ultra (right) and DSQ II (left),
PAS: The portable aerosol spectrometer that is available for this project is a Grimm Aerosol
model 1.108. These devices function by using an internal pump to draw a known flow rate of
ambient air in for sampling. As the sample passes through, it travels perpendicular to the path of
a semiconductor laser beam and scatters the laser light. The scattered-light signal is detected and
quantified with a diode. The diode signals are then processed into distinct channels,
corresponding to the particle size boxes24. Grimm 1.108 particle size measurements range from
0.23 to 20 microns25. Particle mass for the Grimm is calculated using a particle density
computed from a filter sample collected at the same time as particle number concentrations are
recorded. The total particulate mass collected over the interval of the measurements is used to
deduce average density and calibrate the instrument.
Fig. 7: Schematic of Grimm 1.108 PAS Light Scattering25
APS: Aerodynamic particle sizers determine particulate sizes by measuring particle speed
relative to an accelerating flow, as measured by the time taken for the particle to traverse a
known distance by crossing two laser beams. The lag is proportional to the particle diameter26.
The basis for this relationship are conditions of Stokes flow, low Reynolds number (Re < 1)
behavior where the drag force per Stokes' Law is a function of particle aerodynamic diameter
(Dpa), fluid viscosity (μ), fluid far-field velocity (u), and the slip correction factor (Cc), typically
only applied to particles below 10 microns in diameter.
Fdrag = (3*π *μ *Dp*u)/Cc27
For the regime of flows where the Reynolds number exceeds unity, Stokes flow does not
properly apply and the aerodynamic particle diameter becomes a function of particle density.
With a known aerosol density, however, it is possible to generate calibration curves to correct for
this distortion and map average values of particle speed and acceleration with flow conditions to
a particle diameter26. The TSI model 3321 APS is capable of measuring particulate aerodynamic
diameters from 0.5 to 20 microns and can also measure from 0.37 to 20 microns in diameter
using light scattering, as with the APS17.
Fig. 8: TSI Model 3321 APS17
FMPS: Another particle-measuring device, FMPS uses electrometers to determine particle size
distribution from electrical mobility. FMPS detects smaller particles than either APS or PAS,
ranging over 5.6 to 560 nanometers in diameter18. Particle diameter can be determined from an
electric field (E), particle velocity (ve), the slip correction factor, and the carrier fluid viscosity
for low Reynolds numbers.
ve = Be*E = (q*Cc*E)/(3*π*μ*Dp)27
To classify and count particles, a corona charger is used to ionize the incoming particle sin the
sample stream. Filtered air is added to the stream to transport the sample past a repelling electric
field. The particles turn away from the field and strike elctrometers in accordance with their
electrical mobility (Be in the above equation). The greater the electrical mobility, the more
rapidly the particle will be deflected and the sooner it will strike an electrometer. These signals
can be processed to create a particle size distribution18.
Fig. 9: FMPS Operational Schematic from TSI Model 309118
Fig. 10: TSI Model 3091 FMPS18
CO/CO2 Sensor: Hand-held sensor units, such as the TSI IAQ-CALC 7545, use a non-
dispersive infrared (NDIR) sensor to detect CO2 and an electrochemical sensor to detect CO13.
The use of NDIR to detect CO2 is essentially the same procedure as in the FTIR. The
concentration of carbon dioxide is determined from the attenuation of a particular wavelength of
light, per Beer's Law. Electrochemical sensors determine concentration from the current that
results as the gas is either oxidized or reduced on an electrode within the device.
Fig. 11: TSI IAQ-CALC 7545 CO/CO2 Monitor13
Filters: Filter collection of samples is accomplished by drawing a sample, using a pump, through
a filter. Known flow rates are required to relate the collected material to the exhaust stream or
ambient conditions. Filter collection may be integrated with another device. For the purposes of
this project, filter collection is included in the Grimm 1.108 PAS, which has a mount for
collecting particulates on a PTFE filter after they have passed through the scattering
measurement24. Filters are available in multiple materials and selection criteria should be based
on the kind of test to be performed and also on extraction technique. Test selection criteria
include filtering efficiency, removing a sufficient number of particles, mechanical, chemical and
temperature stability, meaning the filters should not react or degrade during the test, and 'blank
correction' the filters should not contain large quantities of the components expected to be
Once particles have been collected on the filter, several tests may be performed. Gravimetric
analysis can determine the particle mass concentration during sampling. This is done by
weighing the filter before and after sampling to determine the total mass of particulates collected,
and dividing by the product of the filter flow rate and time during which the sample was
collected to obtain a mass of particulates per volume. Detailed procedures are available to
perform these analyses and minimize variations, such as those offered by the EPA. Chemical
analysis of the particulates is also well documented. For analysis of inorganics, EPA procedures
document both microwave and hot acid28 extraction techniques. When the filters are to be
dissolved for analysis, filter and solvent compatibility is required29.
Analysis of inorganics per EPA standards is carried out by one of six techniques: Flame and
graphite furnace atomic absorption spectroscopy (FAA/GFAA), X-Ray fluorescence
spectroscopy (XRF), Inductively coupled plasma atomic emission spectroscopy (ICP),
Inductively coupled plasma/mass spectrometry (ICP/MS), Proton induced X-Ray emission
spectroscopy (PIXE), or Neutron activation Analysis (NAA). These methods are summarized in
the indicated reference, the chapter IO-3 overview, and are covered in detail in EPA Methods IO-
3.2 to IO-3.7, respectively30. The preceding methods are not particularly relevant to this project,
as inorganic content of the particulates is not a prescribed measurement for the emissions system.
For samples anticipated to contain volatile organics, a higher degree of control is required to
protect the samples in handling and analysis. Preparation, handling and holding times for such
samples are also governed by EPA procedures31. Choice of extraction method for organics is
dependent on the exact nature of the organics to be measured, but the EPA specifies microwave
extraction, ultrasonic extraction, solvent dilution, or supercritical fluid extraction (SFE) for use
with solid semivolatile and non-volatile organics and SFE for use with solid PAH32. When
extracting for VOC analysis by GC/MS, the specific compound for which the sample is to be
analyzed will determine the preparation method33. The same is true for GC/MS analysis of
PAH34,35. Published work includes detailed descriptions of filter preparation and handling,
sample collection, extraction and analysis by GC/MS36. Solid OC may also be collected and
analyzed from filters, but care must be taken that the values are not overestimated due to gaseous
adsorption on the filter37. Determination of EC and OC content of quartz filter samples is most
popularly carried out with thermal optical reflectance (TOR) or thermal manganese oxidation
Relating Data
Once data has been collected from the various devices, it must be related back to the emissions
source. Depending on whether the emissions were collected via the dilution tunnel, directly from
the exhaust stack or an ambient sample, there are techniques for relating the emitter and the
In the case of dilution tunnel sampling, the exhaust entering the dilution tunnel is has not been
mixed with surrounding air. By knowing the ratio of the exhaust flow entering the tunnel to the
dilution air, a scaling factor for the concentration may be developed the dilution ratio. Any
recorded concentration from the dilution tunnel, times the reciprocal of the dilution ratio, is the
original concentration in the exhaust, assuming that all components are well-mixed. This
assumption can be tested both by injecting known concentrations of trace gases or by
computational fluid dynamics modeling. In our case, modeling was performed to verify the
findings of the Carnegie Mellon researchers who designed the original tunnel. Further, by
knowing the total exhaust flow and the ratio of the sampled exhaust flow to the total, the total
emissions of the burner may be related to the operational conditions.
For ambient measurements, a common techniques is to relate measured pollutant levels to the
quantity of fuel consumed, either on a mass or energy basis. This may be accomplished with a
carbon balance. First, background levels of all pollutants, CO and CO2 are measured. These
same values are measured again while the burner is running. To analyze the data, the
background values are subtracted from the measured values during burner operation. The total
increase in carbon, measured from CO and CO2, is computed as mass and divided by the carbon
mass fraction of the fuel to determine the mass of fuel which contributed to the measured
increase in pollutant levels. Each value can then be related as a ratio, an increase of pollutant per
mass of fuel9. To give the emission factor on an energy basis, the mass of fuel is multiplied by
the heating value to give an energy contribution.
Recent work on this project has included ambient measurements of a prototype burner. A PAS
and hand-held CO, CO2 monitor were used to collect particulate emission factors. Performing
the carbon balance, emission factors for total suspended particles (TSP), PM10 and PM2.5 were
obtained both on mass and energy bases. Satisfactory results were achieved and are shown
below. These data must be qualified, however. The Grimm 1.108 model used to collect particle
counts was not calibrated for particle mass. As a result, the data below assume a particle specific
gravity of 0.5.
Fig. 12: Emission factors, mass-based, during burner operation
A suitable system design and plan have been provided for conducting emissions testing of a solid
biomass burner. CO, CO2, NOx, SOx, PAH, VOC, EC, OC, PM2.5, and particle size distribution
will be measured using FTIR and GC-MS to evaluate gas concentrations, particle sizers, such as
APS, PAS and FMPS to collect information of particle size distributions and masses, and
analysis of solids collected on filters to determine VOC, PAH, EC and OC content. Ambient
monitoring has been related to burner operation through the use of emission factors and direct
sampling from the exhaust stack with a dilution tunnel will be applied in the future to conduct
further measurements of all pollutants of interest.
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Full-text available
Motor vehicles are a significant source of fine carbonaceous particle emissions. Fuels have been reformulated and vehicle technologies have advanced, so an updated assessment of vehicular emissions is needed. Gas- and particle-phase pollutant concentrations were measured in the Caldecott Tunnel in the San Francisco Bay Area during the summer of 1996. Separate samples were collected for uphill traffic in two tunnel bores:  one bore was influenced by heavy-duty diesel truck emissions; a second bore was reserved for light-duty vehicles. Fine particle black carbon and PAH concentrations were normalized to fuel consumption to compute emission factors. Light-duty vehicles and heavy-duty diesel trucks emitted, respectively, 30 ± 2 and 1440 ± 160 mg of fine black carbon particles per kg of fuel burned. Diesel trucks were the major source of lighter PAH, whereas light-duty gasoline vehicles were the dominant source of higher molecular weight PAH such as benzo[a]pyrene and dibenz[a,h]anthracene. Size-resolved measurements of particulate PAH showed significant fractions of diesel-derived PAH to be present in both the ultrafine size mode (<0.12 μm) and the ac cumulation mode (0.12−2 μm). In contrast, gasoline engine-derived PAH emissions were found almost entirely in the ultrafine mode.
A common method for measuring the mass of organic carbon in airborne particulate matter involves collection on a quartz filter and subsequent thermal analysis. If unaccounted for, the adsorption of organic gases onto quartz filters will lead to the overestimation of aerosol organic carbon concentrations (positive artifact). A recommended method of correction for the positive artifact involves sampling with a backup filter. Placed behind either the primary quartz filter, or behind a Teflon filter and collected in parallel with the primary quartz filter, the carbon content of the quartz backup filter is a measure of the adsorbed organic material on the primary quartz filter. In this paper, we illustrate the application of this technique to samples collected in Berkeley, California. While the tandem quartz filter method can be successfully applied to correct for the positive artifact, we discuss two cases when this method will fail. We have found that the capacity for adsorption of organic gases is not uniform for all filters. Instead, filters manufactured by the same company, but having different lot numbers, exhibit variable adsorption capacity. Thus, a filter pair composed of filters from different lots may lead to significant under- or overestimation of particulate organic carbon concentration. Additionally, we have observed that the tandem filter method under-corrects for the positive artifact if the sampling time is short (few hours). Laboratory experiments with vapors of single organic compounds corroborate results based on ambient samples. The evolution of adsorbed organic gases, particularly polar compounds, during thermal analysis indicates that a single compound may experience two distinct adsorbent–adsorbate binding energies. Adsorbed gases may co-evolve with particles at temperatures in excess of 250°C.
Biomass is the most important renewable energy option at present and is expected to maintain that position during the first half of this century. Forest and wood process residues can be converted into useful bioenergy. The structural components of wood are cellulose, hemicelluloses, and lignin. Fuelwoods are composed of biopolymers that consist of various types of cells and the cell walls are built of cellulose, hemicelluloses, and lignin. The fuel properties of wood can be summarized by elemental and proximate analyses and determination of heating value. Cellulose has a smaller heating value than lignin because of its higher degree of oxidation. Elemental H and C contents of fuel and lower degrees of oxidation tend to raise the heating value of the biomass. Woods are either hardwoods or softwoods. Softwood species generally have higher carbon content and higher heating values than hardwood species because of the presence of more lignin and resinous materials in softwood species. Extractives raised the higher heating values of the wood fuels. Heating value of a wood fuel decreases with increasing of moisture content of the wood.
The size and complexity of current dilution samplers is a major barrier to more wide-spread application of these systems for source characterization. A new, more portable dilution sampler has been designed to provide measurements consistent with the widely cited Caltech dilution sampler. Intercomparison experiments were performed using a diesel engine and wood stove to evaluate the comparability of the new design with a sampler based on the Caltech design. These experiments involved simultaneous operation of multiple dilution samplers from the same source. Filter based measurements included PM 2.5 mass, organic carbon, and elemental carbon emissions. Particle size distributions in the range from 10–480 nm were measured using a scanning mobility particle sizer. The filter-based and integrated-total volume measurements made with the two designs are in good agreement. For example, the average relative bias between the two samplers of PM 2.5 mass emission rate measured with Teflon filters is 1%. Nucleation was intermittently observed in the sampler based on the Caltech design, but rarely observed in the new design. Significant discrepancies in total number emissions between the two samplers occurred during periods of nucleation. Experiments were also conducted to examine the effects of residence time on the diluted emissions. No changes in the filter-based or integrated volume measurements were observed with an additional 40-s residence time, indicating that phase equilibrium is established in the 2.5 s of residence time provided by the dilution tunnel. This conclusion is consistent with theoretical analysis. These results provide new insight into the effects of dilution sampling on measurements of fine particle emissions, providing important data for the ongoing effort of the EPA and ASTM to define a standardized dilution sampling methodology for characterizing emissions from stationary combustion sources.
An analytical formula has been derived to calculate the calibration curve for particles of any given density from the calibration curve for an aerosol of a different density. The Aerodynamic Particle Sizer is based on the principle that particles accelerated from a nozzle will lag the flow, depending on their aerodynamic diameter. Because of the high flow velocity, the particle acceleration is beyond the Stokes regime, leading to a dependence on particle density. The correction formula is justified by a combination of analysis and numerical trajectory computations. The density effect is appreciable. For example, if the instrument is calibrated with unit density aerosol, 20-μm particles of density 4.0 will be oversized by 20%. The corrected calibration curves are in agreement with measurements by Baron (1984).
Fine particle formation in wood combustion was studied in a laboratory scale laminar flow reactor at various flue gas chlorine and sulphur concentrations. Aerosol samples were quenched at around 850 °C using a porous tube diluter. Fine particle number concentrations, mass concentrations, size distributions and chemical compositions were measured. In addition, flue gas composition, including SO2 and HCl, was monitored. Experimental results were interpreted by thermodynamic equilibrium calculations.Addition of HCl clearly raised fine particle mass concentration (PM1.0) which was because of increased release of ash-forming material to fine particles. Especially the release of K, Na, Zn and Cd to fine particles increased. These species form chlorides which apparently increases their volatilization from the fuel. When a sufficient amount of SO2 was supplied in a chlorine rich combustion (S/Cl molar ratio from 4.7 to 7.5), most of the HCl stayed in the gas phase, release of ash-forming elements decreased and also fine particle concentrations dropped significantly. The sulphation of alkali metals is suggested to play a key role in the observed decrease in the fine particle concentration. It seems that the formation of sulphates leads to alkali metal retention in the coarse particle fraction.
Particle and gaseous emissions of a top-feed pellet stove were studied in laboratory conditions. Pellets made of separate stem and bark materials of five different wood species and a commercial pellet product were used as fuels. The study included the determination of the particle number concentration, size distribution, fine-particle mass (PM1.0), CO, CO2, NOx, and volatile organic compounds (VOC). The PM1.0 emission was analyzed for inorganic substances, organic carbon, and elemental carbon. Thermodynamic equilibrium calculations were performed to interpret the results from chemical analysis and to estimate the chemical composition of the PM1.0 mass emitted with various fuels. The bark fuels produced higher PM, VOC, and CO emissions than stem fuels. This was evidently related to the higher ash content of the bark fuels and was found to increase both the fly ash emission and the products of incomplete combustion. The fuel ash content correlated linearly with the PM1.0 emission. Among stem fuels, willow and alder produced higher PM1.0 emissions than birch, pine, spruce, and the commercial fuel. An exceptionally low PM1.0 emission was measured from pine bark combustion, which can be explained by the low ash content of the fuel. The main components in the PM1.0 were K2SO4, KCl, K2CO3, KOH, and organic material. Except birch fuels, around 60−80 mass % of potassium species were K2SO4 based on the equilibrium calculations. In the case of birch fuels, because of the high chlorine content and low S/Cl ratios, around half of the potassium was KCl.
A combustion test has been made with residues from hydrolysis of wood for fuel ethanol production. A 150 kW powder burner was used. Fuel feeding and combustion were stable. The average concentration of CO in the stack gas was 8 mg/MJ, the average concentration of NO x was 59 mg/MJ and the average total hydrocarbon concentration was below 1 ppm, at an average O 2 -concentration of 4.6%. The low contents of potassium and sodium in the hydrolysis residue make the material attractive as a gas turbine fuel and the conclusion of this test is that direct combustion may be a feasible approach for gas turbine applications.