Designing ambient particulate matter monitoring program for source apportionment study by receptor modeling

Particulate matter (PM) receptor modeling requires specific intensive input data that is always a challenge to produce cost effectively. A well-designed monitoring program is important to collect such PM ambient data in urban areas with diverse and densely distributed sources. This paper presents a general framework for designing such a monitoring program while emphasizing appropriate quality assurance and quality control elements that are particularly applicable where limited resources are available. Topics for discussion include selection of monitoring sites, sampling and analytical techniques, and the uncertainty estimation for ambient concentration input data. The design framework is illustrated by a case study of a monitoring program for PM source apportionment in the Bangkok Metropolitan Region in which 24-h fine and coarse PM samples were collected using two collocated dichotomous samplers. Comparison between black carbon measurements by Smoke Stain reflectometry and Thermal Optical Transmittance method is highlighted.     

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.     

Performance characteristics of PM10 samplers under calm air conditions

The size range of airborne particles that is closely related to specific deposition regions in the human respiratory tract and excess lung burden of these deposited particles is associated with disease. Size-selective sampling, therefore, needs to be performed to assess the related health risks. Performance criteria applied to these samplers must be well characterized in order to provide accurate and reliable results. The PM10 samplers that have been used in place of the total suspended particulate samplers for the collection of ambient air particles are more relevant to potential inhalation hazards. In order to be certified, a PM10 sampler must meet reliable performance specifications, primarily the aerosol penetration test with liquid and solid particles in a wind tunnel (wind speeds of 2, 8, and 24 km/hr). This testing is intended to assure reasonable accuracy in aerosol measurements. However, the sampler performance under calm air conditions has not been well studied. In the present study, the sampling heads of three devices--the Harvard impactor, the Personal Environmental Monitor (PEM), and the Sierra Andersen model 241 dichotomous sampler PM10 inlet head--were tested for aerosol separation efficiency. With the consideration of bias and imprecision of the measurements, five specimens of each type of sampler were chosen for performance testing, repeating the tests 5 times for each specimen. An ultrasonic atomizing nozzle was used to nebulize potassium sodium tartrate tetrahydrate and dioctyl phthalate particles as the solid and liquid challenge aerosols, respectively. The aerosol number concentrations and size distributions upstream and downstream of the samplers were measured by using an aerosizer calibrated against a settling velocity chamber. The results showed that among the samplers tested, the dichotomous sampler PM10 inlet head had the best fit to the PM10 convention, while the other two samplers not only appeared to have a steeper separation-curve slope but also had significant particle bounce when challenged with solid particles. Analysis of variance also confirmed the superiority of the dichotomous samplers. Surface-coating with oil or grease greatly reduced the problem of particle bounce.     

Performance evaluation of six different aerosol samplers in a particulate matter generation chamber

The present study was carried out with the aim of evaluating the performance of six different aerosol samplers in terms of mass concentration, particle size distribution, and mass fraction for the international size-sampling conventions. The international size-sampling criteria were defined as inhalable, thoracic, and respirable mass fractions with 50% cutoff at an aerodynamic equivalent diameter of 100 μm, 10 μm, and 4 μm, respectively. Two Andersen, four total suspended particulate (TSP), two RespiCon, four PM₁₀, two DustTrak, and two SidePak samplers were selected and tested to quantitatively estimate human exposure in a carefully controlled particulate matter (PM) test chamber. The overall results indicate that (1) Andersen samplers underestimate total suspended PM and overestimate thoracic and respirable PM due to particle bounce and carryover between stages, (2) TSP samplers provide total suspended PM as reference samplers, (3) TSP samplers quantified by a coulter counter multisizer provide no information below an equivalent spherical diameter of 2 μm and therefore underestimate respirable PM, (4) RespiCon samplers are free from particle bounce as inhalable samplers but underestimate total suspended PM, (5) PM₁₀ samplers overestimate thoracic PM, and (6) DustTrak and SidePak samplers provide relative PM concentrations instead of absolute PM concentrations.     

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.     

Concentrations of particulate matter emitted from large cattle feedlots in Kansas

Particulate matter (PM) emitted from cattle feedlots are thought to affect air quality in rural communities, yet little is known about factors controlling their emissions. The concentrations of PM (i.e., PM2.5, PM10, and total suspended particulates or TSP) upwind and downwind at two large cattle feedlots (KS1, KS2) in Kansas were measured with gravimetric samplers from May 2006 to October 2009 (at KS1) and from September 2007 to April 2008 (at KS2). The mean downwind and net (i.e., downwind - upwind) mass concentrations of PM2.5, PM10, and TSP varied seasonally, indicating the need for multiple-day, seasonal sampling. The downwind and net concentrations were closely related to the moisture content of the pen surface. The PM2.5/PM10 and PM2.5/TSP ratios at the downwind sampling location were also related to the moisture content of the pen surface, humidity, and temperature. Measurement of the particle size distribution downwind of the feedlot with a cascade impactor showed geometric mean diameter ranging from 7 to 18 microm, indicating that particles that were emitted from the feedlots were generally large in size.     

Exposure of chronic obstructive pulmonary disease patients to particulate matter: relationships between personal and ambient air concentrations

Mot time-series studies of particulate air pollution and acute health outcomes assess exposure of the study population using fixed-site outdoor measurements. To address the issue of exposure misclassification, we evaluate the relationship between ambient particle concentrations and personal exposures of a population expected to be at risk of particle health effects. Sampling was conducted within the Vancouver metropolitan area during April-September 1998. Sixteen subjects (non-smoking, ages 54-86) with physician-diagnosed chronic obstructive pulmonary disease (COPD) wore personal PM2.5 monitors for seven 24-hr periods, randomly spaced approximately 1.5 weeks apart. Time-activity logs and dwelling characteristics data were also obtained for each subject. Daily 24-hr ambient PM10 and PM2.5 concentrations were measured at five fixed sites spaced throughout the study region. SO4(2-), which is found almost exclusively in the fine particle fraction and which does not have major indoor sources, was measured in all PM2.5 samples as an indicator of accumulation mode particulate matter of ambient origin. The mean personal and ambient PM2.5 concentrations were 18 micrograms/m3 and 11 micrograms/m3, respectively. In analyses relating personal and ambient measurements, ambient concentrations were expressed either as an average of the values obtained from five ambient monitoring sites for each day of personal sampling, or as the concentration obtained at the ambient site closest to each subject's home. The mean personal to ambient concentration ratio of all samples was 1.75 (range = 0.24 to 10.60) for PM2.5, and 0.75 (range = 0.09 to 1.42) for SO4(2-). Regression analyses were conducted for each subject separately and on pooled data. The median correlation (Pearson's r) between personal and average ambient PM2.5 concentrations was 0.48 (range = -0.68 to 0.83). Using SO4(2-) as the exposure metric, the median r between personal and average ambient concentrations was 0.96 (range = 0.66 to 1.0). Use of the closest ambient site did not improve the median correlation of the group for either PM2.5 or SO4(2-). All pooled analyses resulted in lower correlation coefficients than the median correlation coefficient of individual regressions. Personal SO4(2-) was more highly correlated with all ambient measures than PM2.5. Inclusion of time-activity and dwelling characteristics data did not result in a useful predictive regression model for PM2.5 personal exposure, but improved the model fit from simply regressing against ambient concentration (R2 = 0.27). The model for SO4(2-) was predictive (R2 = 0.82), as personal exposures were largely explained by ambient levels. These results indicate a relatively low correlation between personal exposure and ambient PM2.5 that is not improved by assigning exposure to the closest ambient monitor. The correlation between personal exposure and ambient concentration is high, however, when using SO4(2-), an indicator of accumulation mode particulate matter of ambient origin.     

A new methodological approach: The combined use of two-stage streaker samplers and optical particle counters for the characterization of airborne particulate matter

We describe a new experimental methodology based on the contemporary use of two-stage continuous streaker samplers and optical particle counters. This is a complementary approach to size-segregated particulate matter (PM) sampling, and it is able to give information on the elemental size distribution and to assess the contribution of major PM source to size bins. PM samples in the fine and coarse fraction of PM10 have been collected by a two-stage streaker sampler and analyzed by particle-induced X-ray emission (PIXE) to obtain elemental concentration time series with hourly resolution. PM sources and profiles were singled out by positive matrix factorization (PMF). A multi-linear regression of size-segregated number of particles versus the sources, resolved by PMF, made possible the apportionment of size-segregated particles number in a fast and direct way. Results obtained in three sampling sites, located in different urban districts are discussed.     

Daily mortality in the Philadelphia metropolitan area and size-classified particulate matter

Time-series of daily mortality data from May 1992 to September 1995 for various portions of the seven-county Philadelphia, PA, metropolitan area were analyzed in relation to weather and a variety of ambient air quality parameters. The air quality data included measurements of size-classified PM, SO4(2-), and H+ that had been collected by the Harvard School of Public Health, as well as routine air pollution monitoring data. Because the various pollutants of interest were measured at different locations within the metropolitan area, it was necessary to test for spatial sensitivity by comparing results for different combinations of locations. Estimates are presented for single pollutants and for multiple-pollutant models, including gaseous pollutants and mutually exclusive components of PM (PM2.5 and coarse particles, SO4(2-) and non-SO4(2-) portions of total suspended particulate [TSP] and PM10), measured on the day of death and the previous day. We concluded that associations between air quality and mortality were not limited to data collected in the same part of the metropolitan area; that is, mortality for one part may be associated with air quality data from another, not necessarily neighboring, part. Significant associations were found for a wide variety of gaseous and particulate pollutants, especially for peak O3. Using joint regressions on peak O3 with various other pollutants, we found that the combined responses were insensitive to the specific other pollutant selected. We saw no systematic differences according to particle size or chemistry. In general, the associations between daily mortality and air pollution depended on the pollutant or the PM metric, the type of collection filter used, and the location of sampling. Although peak O3 seemed to exhibit the most consistent mortality responses, this finding should be confirmed by analyzing separate seasons and other time periods.     

Comparison of real-time instruments used to monitor airborne particulate matter

Measurements collected using five real-time continuous airborne particle monitors were compared to measurements made using reference filter-based samplers at Bakersfield, CA, between December 2, 1998, and January 31, 1999. The purpose of this analysis was to evaluate the suitability of each instrument for use in a real-time continuous monitoring network designed to measure the mass of airborne particles with an aerodynamic diam less than 2.5 microns (PM2.5) under wintertime conditions in the southern San Joaquin Valley. Measurements of airborne particulate mass made with a beta attenuation monitor (BAM), an integrating nephelometer, and a continuous aerosol mass monitor (CAMM) were found to correlate well with reference measurements made with a filter-based sampler. A Dusttrak aerosol sampler overestimated airborne particle concentrations by a factor of approximately 3 throughout the study. Measurements of airborne particulate matter made with a tapered element oscillating microbalance (TEOM) were found to be lower than the reference filter-based measurements by an amount approximately equal to the concentration of NH4NO3 observed to be present in the airborne particles. The performance of the Dusttrak sampler and the integrating nephelometer was affected by the size distribution of airborne particulate matter. The performance of the BAM, the integrating nephelometer, the CAMM, the Dusttrak sampler, and the TEOM was not strongly affected by temperature, relative humidity, wind speed, or wind direction within the range of conditions encountered in the current study. Based on instrument performance, the BAM, the integrating nephelometer, and the CAMM appear to be suitable candidates for deployment in a real-time continuous PM2.5 monitoring network in central California for the range of winter conditions and aerosol composition encountered during the study.     

Uncertainty associated with the gravimetric measurement of particulate matter concentration in ambient air

This work applied a propagation of uncertainty method to typical total suspended particulate (TSP) sampling apparatus in order to estimate the overall measurement uncertainty. The objectives of this study were to estimate the uncertainty for three TSP samplers, develop an uncertainty budget, and determine the sensitivity of the total uncertainty to environmental parameters. The samplers evaluated were the TAMU High Volume TSP Sampler at a nominal volumetric flow rate of 1.42 m³ min^–1 (50 CFM), the TAMU Low Volume TSP Sampler at a nominal volumetric flow rate of 17 L min^–1 (0.6 CFM) and the EPA TSP Sampler at the nominal volumetric flow rates of 1.1 and 1.7 m³ min^–1 (39 and 60 CFM). Under nominal operating conditions the overall measurement uncertainty was found to vary from 6.1 x 10^–6 g m^–3 to 18.0 x 10^–6 g m^–3, which represented an uncertainty of 1.7% to 5.2% of the measurement. Analysis of the uncertainty budget determined that three of the instrument parameters contributed significantly to the overall uncertainty: the uncertainty in the pressure drop measurement across the orifice meter during both calibration and testing and the uncertainty of the airflow standard used during calibration of the orifice meter. Five environmental parameters occurring during field measurements were considered for their effect on overall uncertainty: ambient TSP concentration, volumetric airflow rate, ambient temperature, ambient pressure, and ambient relative humidity. Of these, only ambient TSP concentration and volumetric airflow rate were found to have a strong effect on the overall uncertainty. The technique described in this paper can be applied to other measurement systems and is especially useful where there are no methods available to generate these values empirically.

Implications:?This work addresses measurement uncertainty of TSP samplers used in ambient conditions. Estimation of uncertainty in gravimetric measurements is of particular interest, since as ambient particulate matter (PM) concentrations approach regulatory limits, the uncertainty of the measurement is essential in determining the sample size and the probability of type II errors in hypothesis testing. This is an important factor in determining if ambient PM concentrations exceed regulatory limits. The technique described in this paper can be applied to other measurement systems and is especially useful where there are no methods available to generate these values empirically.     

Comparison of particle light scattering and fine particulate matter mass in central California

Particle light scattering (Bsp) from nephelometers and fine particulate matter (PM2.5) mass determined by filter samplers are compared for summer and winter at 35 locations in and around California's San Joaquin Valley from December 2, 1999 to February 3, 2001. The relationship is described using particle mass scattering efficiency (sigmasp) derived from linear regression of Bsp on PM2.5 that can be applied to estimated PM2.5 from nephelometer data within the 24-hr filter sampling periods and between the every-6th-day sampling frequency. An average of sigmaSp = 4.9 m2/g was found for all of the sites and seasons; however, sigmasp averaged by site type and season provided better PM2.5 estimates. On average, the sigmasp was lower in summer than winter, consistent with lower relative humidities, lower fractions of hygroscopic ammonium nitrate, and higher contributions from fugitive dust. Winter average sigmasp were similar at non-source-dominated sites, ranging from 4.8 m2/g to 5.9 m2/g. The sigmasp was 2.3 m2/g at the roadside, 3.7 m2/g at a dairy farm, and 4.1 m2/g in the Kern County oilfields. Comparison of Bsp from nephelometers with and without a PM2.5 inlet at the Fresno Supersite showed that coarse particles contributed minor amounts to light scattering. This was confirmed by poorer correlations between Bsp and coarse particulate matter measured during a fall sampling period.     

Ammonia concentrations and modeling of inorganic particulate matter in the vicinity of an egg production facility in Southeastern USA

Ammonia (NH₃) is an important base gas and can react with acidic species to form atmospheric aerosols. Due to the rapid growth of poultry and swine production in the North Carolina Coastal Plain, atmospheric NH₃ concentrations across the region have subsequently increased. Ammonia concentrations and inorganic particulate matter (PM) at four ambient stations in the vicinity of an egg production facility were measured for 1 year using PM_2.5 speciation samplers with honeycomb denuders and ion chromatography (IC). Meanwhile, concentrations of NH₃ and inorganic PM in one of the egg production houses were also simultaneously measured using a gas analyzer for NH₃ and the filter pack plus IC method for inorganic PM. An equilibrium model-ISORROPIA II was applied to predict the behavior of inorganic aerosols in response to precursor gas concentrations and environmental parameters. Average ambient NH₃ concentrations varied from 10.0 to 27.0 μg/m³, and they were negatively correlated with the distances from the ambient location to the nearest egg production house exhausts. Ambient NH₃ concentrations were higher in warm seasons than in cold seasons. Measured NH₃ concentrations agreed well with ISORROPIA II model predictions at all sampling stations. For the ambient stations, there was a good agreement in particle phase NH₄ ⁺ between the model simulation and observations. For the in-house station, the model simulation was applied to correct the overestimation of particle phase NH₄ ⁺ due to gas phase NH₃ breaking through the denuders. Changes in SO₄ ^2?, NO₃ ^?, and Cl^? yield proportional changes in inorganic PM mass. Due to the abundance of NH₃ gas in the vicinity area of the monitored farm, changes in NH₃ concentrations had a small effect on inorganic PM mass. Aerosol equilibrium modeling may be used to assess the influence of precursor gas concentrations on inorganic PM formation when the measurements for some species are unavailable.     

Effects of sulfur dioxide and oxides of nitrogen emission reductions on fine particulate matter mass concentrations: regional comparisons

Two thermodynamic equilibrium models were applied to estimate changes in mean airborne fine particle (PM2.5) mass concentrations that could result from changes in ambient concentrations of sulfate, nitric acid, or ammonia in the southeastern United States, the midwestern United States, and central California. Pronounced regional differences were found. Southeastern sites exhibited the lowest current mean concentrations of nitrate, and the smallest predicted responses of PM2.5 nitrate and mass concentrations to reductions of nitric acid, which is the principal reaction product of the oxidation of nitrogen dioxide (NO2) and the primary gas-phase precursor of fine particulate nitrate. Weak responses of PM2.5 nitrate and mass concentrations to changes in nitric acid levels occurred even if sulfate concentrations were half of current levels. The midwestern sites showed higher levels of fine particulate nitrate, characterized by cold-season maxima, and were projected to show decreases in overall PM levels following decreases of either sulfate or nitric acid. For some midwestern sites, predicted PM2.5 nitrate concentrations increased as modeled sulfate levels declined, but sulfate reductions always reduced the predicted fine PM mass concentrations; PM2.5 nitrate concentrations became more sensitive to reductions of nitric acid as modeled sulfate concentrations were decreased. The California sites currently have the highest mean concentrations of fine PM nitrate and the lowest mean concentrations of fine PM sulfate. Both the estimated PM2.5 nitrate and fine mass concentrations decreased in response to modeled reductions of nitric acid at all California sites. The results indicate important regional differences in expected PM2.5 mass concentration responses to changes in sulfate and nitrate precursors. Analyses of ambient data, such as described here, can be a key part of weight of evidence (WOE) demonstrations for PM2.5 attainment plans. Acquisition of the data may require special sampling efforts, especially for PM2.5 precursor concentration data.     

Source profiles of particulate matter emissions from a pilot-scale boiler burning North American coal blends.

Recent awareness of suspected adverse health effects from ambient particulate matter (PM) emission has prompted publication of new standards for fine PM with aerodynamic diameter less than 2.5 microm (PM2.5). However, scientific data on fine PM emissions from various point sources and their characteristics are very limited. Source apportionment methods are applied to identify contributions of individual regional sources to tropospheric particulate concentrations. The existing industrial database developed using traditional source measurement techniques provides total emission rates only, with no details on chemical nature or size characteristics of particulates. This database is inadequate, in current form, to address source-receptor relationships. A source dilution system was developed for sampling and characterization of total PM, PM2.5, and PM10 (i.e., PM with aerodynamic diameter less than 10 pm) from residual oil and coal combustion. This new system has automatic control capabilities for key parameters, such as relative humidity (RH), temperature, and sample dilution. During optimization of the prototype equipment, three North American coal blends were burned using a 0.7-megawatt thermal (MWt) pulverized coal-fired, pilot-scale boiler. Characteristic emission profiles, including PM2.5 and total PM soluble acids, and elemental and carbon concentrations for three coal blends are presented. Preliminary results indicate that volatile trace elements such as Pb, Zn, Ti, and Se are preferentially enriched in PM2.5. PM2.5 is also more concentrated in soluble sulfates relative to total PM. Coal fly ash collected at the outlet of the electrostatic precipitator (ESP) contains about 85-90% PM10 and 30-50% PM2.5. Particles contain the highest elemental concentrations of Si and Al while Ca, Fe, Na, Ba, and K also exist as major elements. Approximately 4-12% of the materials exists as soluble sulfates in fly ash generated by coal blends containing 0.2-0.8% sulfur by mass. Source profile data for an eastern U.S. coal show good agreement with those reported from a similar study done in the United States. Based on the inadequacies identified in the initial sampling equipment, a new, plume-simulating fine PM measurement system with modular components for field use is being developed for determining coal combustion PM source profiles from utility boiler stacks.     

Spatial and temporal variability in urban fine particulate matter concentrations

Identification of hot spots for urban fine particulate matter (PM(2.5)) concentrations is complicated by the significant contributions from regional atmospheric transport and the dependence of spatial and temporal variability on averaging time. We focus on PM(2.5) patterns in New York City, which includes significant local sources, street canyons, and upwind contributions to concentrations. A literature synthesis demonstrates that long-term (e.g., one-year) average PM(2.5) concentrations at a small number of widely-distributed monitoring sites would not show substantial variability, whereas short-term (e.g., 1-h) average measurements with high spatial density would show significant variability. Statistical analyses of ambient monitoring data as a function of wind speed and direction reinforce the significance of regional transport but show evidence of local contributions. We conclude that current monitor siting may not adequately capture PM(2.5) variability in an urban area, especially in a mega-city, reinforcing the necessity of dispersion modeling and methods for analyzing high-resolution monitoring observations.     

Time-series analysis of above-road particulate matter at the Caldecott Tunnel exit

On November 18, 1997, above-road particulate matter (PM) lidar (light detection and ranging) signals and heavy-duty (HD) and light-duty (LD) vehicle counts were simultaneously collected for 894 10-sec sampling periods at the Caldecott Tunnel in Orinda, CA, for the purpose of measuring the relative contributions of LD and HD vehicles to the PM lidar signal under real-world driving conditions. The relationship between the PM lidar signal and traffic activity (i.e., LD and HD traffic volumes) was examined using a time-series analysis technique, multilagged regression. The time-series model results indicate that the PM lidar signal in the current sampling period (PMt) depended on the level recorded in the previous three sampling periods (i.e., PMt-1, PMt-2, and PMt-3), the number of LD vehicles in the seventh past sampling period (LDt-7), and the number of HD vehicles measured 80 sec previous to the current sampling period (HDt-8). On a 10-sec period basis, the model results indicate that HD vehicles contributed, on average, 3 times more to above-road PM lidar signals than did LD vehicles. The observed lag in the relationship between vehicle types and the lidar signal 20 m above the road suggests that resuspended road dust, rather than tailpipe exhaust emissions, was the main source of the detected PM. Detection of road dust at such heights above the road suggests the need for investigating the processes governing the vertical transport and recycling of PM over the road as a function of vehicle dynamics under a range of meteorological conditions.     

Evaluation of solid particle number and black carbon for very low particulate matter emissions standards in light-duty vehicles

To reliably measure at the low particulate matter (PM) levels needed to meet California’s Low Emission Vehicle (LEV III) 3- and 1-mg/mile particulate matter (PM) standards, various approaches other than gravimetric measurement have been suggested for testing purposes. In this work, a feasibility study of solid particle number (SPN, d50 = 23 nm) and black carbon (BC) as alternatives to gravimetric PM mass was conducted, based on the relationship of these two metrics to gravimetric PM mass, as well as the variability of each of these metrics. More than 150 Federal Test Procedure (FTP-75) or Supplemental Federal Test Procedure (US06) tests were conducted on 46 light-duty vehicles, including port-fuel-injected and direct-injected gasoline vehicles, as well as several light-duty diesel vehicles equipped with diesel particle filters (LDD/DPF). For FTP tests, emission variability of gravimetric PM mass was found to be slightly less than that of either SPN or BC, whereas the opposite was observed for US06 tests. Emission variability of PM mass for LDD/DPF was higher than that of both SPN and BC, primarily because of higher PM mass measurement uncertainties (background and precision) near or below 0.1 mg/mile. While strong correlations were observed from both SPN and BC to PM mass, the slopes are dependent on engine technologies and driving cycles, and the proportionality between the metrics can vary over the course of the test. Replacement of the LEV III PM mass emission standard with one other measurement metric may imperil the effectiveness of emission reduction, as a correlation-based relationship may evolve over future technologies for meeting stringent greenhouse standards.

Implications: Solid particle number and black carbon were suggested in place of PM mass for the California LEV III 1-mg/mile FTP standard. Their equivalence, proportionality, and emission variability in comparison to PM mass, based on a large light-duty vehicle fleet examined, are dependent on engine technologies and driving cycles. Such empirical derived correlations exhibit the limitation of using these metrics for enforcement and certification standards as vehicle combustion and after-treatment technologies advance.     

Mass-size distributions of particulate sulfate, nitrate, and ammonium in a particulate matter nonattainment region in southern Taiwan

Concentrations and distributions of three major water-soluble ion species (sulfate, nitrate, and ammonium) contained in ambient particles were measured at three sampling sites in the Kao-ping ambient air quality basin, Taiwan. Ambient particulate matter (PM) samples were collected in a Micro-orifice Uniform Deposit Impactor from February to July 2003 and were analyzed for water-soluble ion species with an ion chromatograph. The PM1/ PM2.5 and PM1/PM10 concentration ratios at the emission source site were 0.73 and 0.53 and were higher than those (0.68 and 0.48) at the background site because there are more combustion sources (i.e., industrial boilers and traffic) around the emission source site. Mass-size distributions of PM NO3- were found in both the fine and coarse modes. SO4(2-)and NH4+ were found in the fine particle mode (PM2.5), with significant fractions of submicron particles (PM1). The source site had higher PM1/PM10(79, 42, and 90%) and PM1/PM2.5 concentration ratios (90, 58, and 93%) for the three major inorganic secondary aerosol components (SO4(2-), NO3-, and NH4+) than the receptor site (65, 27, and 65% for PM1/PM10, 69, 51, and 70% for PM1/PM2.5. Results obtained in this study indicate that the PM1 (submicron aerosol particles) fraction plays an important role in the ambient atmosphere at both emission source and receptor sites. Further studies regarding the origin and formation of ambient secondary aerosols are planned.     

Characteristics of inhalable particulate matter concentration and size distribution from power plants in China

In this investigation, the collection efficiency of particulate emission control devices (PECDs), particulate matter (PM) emissions, and PM size distribution were determined experimentally at the inlet and outlet of PECDs at five coal-fired power plants. Different boilers, coals, and PECDs are used in these power plants. Measurement in situ was performed by an electrical low-pressure impactor with a sampling system, which consisted of an isokinetic sampler probe, precut cyclone, and two-stage dilution system with a sample line to the instruments. The size distribution was measured over a range from 0.03 to 10 microm. Before and after all of the PECDs, the particle number size distributions display a bimodal distribution. The PM2.5 fraction emitted to atmosphere includes a significant amount of the mass from the coarse particle mode. The controlled and uncontrolled emission factors of total PM, inhalable PM (PM10), and fine PM P(M2.5) were obtained. Electrostatic precipitator (ESP) and baghouse total collection efficiencies are 96.38-99.89% and 99.94%, respectively. The minimum collection efficiency of the ESP and the baghouse both appear in the particle size range of 0.1-1 microm. In this size range, ESP and baghouse collection efficiencies are 85.79-98.6% and 99.54%. Real-time measurement shows that the mass and number concentration of PM10 will be greatly affected by the operating conditions of the PECDs. The number of emitted particles increases with increasing boiler load level because of higher combustion temperature. During test run periods, the data reproducibility is satisfactory.