A comprehensive particulate matter monitoring system and dosimetry-based ambient particulate matter standards

A numerical particulate matter (PM) measurement model is developed to characterize and evaluate PM sampling methods. Simulations are conducted using the model to evaluate currently widely used PM samplers, including Federal Reference Method (FRM) samplers. The simulations show that current PM samplers are very vulnerable to both changes in measurement target (i.e., natural variability of particle size distribution) and the sampler's design, manufacturing, and operating conditions, potentially resulting in significant errors in the monitoring data. The numerical model is used in conjunction with two types of commercially available PM monitoring devices to form a Comprehensive Particulate Matter Monitoring System (CPMMS). The first type of device can be any mass-based PM monitor with a well-defined sampling efficiency curve. The second type of device is one capable of measuring particle size distribution with a reasonably good relative accuracy between size categories but not necessarily accurate in measuring absolute mass concentrations. This study shows that CPMMS can produce much higher quality PM monitoring data than the current PM samplers under the same conditions. In addition, unlike past and current PM monitoring data such as total suspended particulates, coarse PM (PM10), fine PM (PM2.5), etc., the CPMMS monitoring data will survive changes in PM regulatory definition. A new concept, dosimetry-based PM metrics and standards, is proposed to define ambient PM level based on the deposition fraction of particles in the human respiratory tract. The dosimetry-based PM metrics is more meaningful because it correlates the ambient PM level with the portion that can be deposited in the respiratory tract without an arbitrary cutoff particle diameter. CPMMS makes dosimetry-based PM metrics and standards feasible.     

Modeling exposure to particulate matter

Exposure assessment, a component of risk assessment, links sources of pollution with health effects. Exposure models are scientific tools used to gain insights into the processes affecting exposure assessment. The purpose of this paper is to review the process and methodology of estimating inhalation exposure to particulate matter (PM) using various types of models. Three types of models are discussed in the paper. Indirect type of models are physical models that employ inventories of outdoor and indoor sources and their emission rates to identify major sources contributing to exposure to PM, and use fate and transport and indoor air quality models to estimate PM concentrations at receptor sites. PM concentrations and time spent by a subject at each receptor site are input variables to the conventional exposure model that estimates the desired exposure levels. Direct type models use measured exposure or exposure concentrations in conjunction with information obtained from questionnaires to formulate exposure regression models. Stochastic models use exposure measurements, estimates can also be used, to formulate exposure population distributions and investigate associated uncertainty and variability. Since models developed using databases from western countries are not necessarily applicable in developing countries, the difference in requirements among western and developing countries is highlighted in the paper. Employment of exposure modeling methods in developing countries requires development of local information. Such information includes local outdoor and indoor source inventories, local or regional meteorological conditions, adjustment of indoor models to reflect local building construction conditions, and use of questionnaires to obtain local time budget and activity patterns of the subject population.     

Journey-time exposure to particulate air pollution

Journey-time exposures to particulate air pollution were investigated in Leicester, UK, between January and March 2005. Samples of TSP, PM₁₀, PM_2.5, and PM₁ were simultaneously collected using light scattering devices whilst journeys were made by walking an in-car. Over a period of two months, 33 pairs of walking and in-car measurements were collected along two circular routes. Average exposures while walking were seen to be higher than those found in-car for each of the particle fractions: average walking to in-car ratios were 1.2 (± 0.6), 1.5 (± 0.6), 1.3 (± 0.6), and 1.4 (± 0.6) μg m⁻³ for coarse (TSP–PM₁₀), intermediate (PM₁₀–PM_2.5), fine (PM_2.5–PM₁), and very fine particles (PM₁), respectively. Correlations between walking and in-car exposures were seen to be weak for coarse particles (r=0.10, p=0.58), moderate for the intermediate particles (r=0.49, p<0.01) but strong for fine (r=0.89, p<0.01) and very fine (r=0.90, P<0.01) particles. PM₁₀ exposures while walking were on average 70% higher than a nearby roadside fixed-site monitor whilst in-car exposures were 25% higher than the same fixed-site monitor. Particles with an aerodynamic diameter of less than 2.5 μm were seen to be highly correlated between walking and in-car particle exposures and a rural fixed-site monitor about 30 km south of Leicester.     

Biomagnetic monitoring of industry-derived particulate pollution

Clear association exists between ambient PM₁₀ concentrations and adverse health outcomes. However, determination of the strength of associations between exposure and illness is limited by low spatial-resolution of particulate concentration measurements. Conventional fixed monitoring stations provide high temporal-resolution data, but cannot capture fine-scale spatial variations. Here we examine the utility of biomagnetic monitoring for spatial mapping of PM₁₀ concentrations around a major industrial site. We combine leaf magnetic measurements with co-located PM₁₀ measurements to achieve inter-calibration. Comparison of the leaf-calculated and measured PM₁₀ concentrations with PM₁₀ predictions from a widely-used atmospheric dispersion model indicates that modelling of stack emissions alone substantially under-predicts ambient PM₁₀ concentrations in parts of the study area. Some of this discrepancy might be attributable to fugitive emissions from the industrial site. The composition of the magnetic particulates from vehicle and industry-derived sources differ, indicating the potential of magnetic techniques for source attribution.     

Policy uses of particulate exposure estimates

This paper reviews the uses of particulate exposure estimates for science and policy. We propose a set of normative factors to guide the selection and application of various approaches for exposure assessment. For exposure estimates intended for use in support of the development or air pollution regulations or selection of control strategies, the proposed criteria include--compatibility with policy scope and scale, cost-effectiveness, characterization of uncertainty, political and institutional feasibility, and sensitivity to framing. For exposure assessment in support of epidemiological research, key criteria are-compatability with the specific hypothesis being tested, and compatibility with the temporal and spatial scale of analysis. The various major approaches for estimation of exposure--direct and indirect measurement, empirical and physical modeling--are catalogued and compared with these proposed criteria.     

Roadside particulate air pollution in Bangkok

Airborne fine particles of PM(2.5-10) and PM2.5 in Bangkok, Nonthaburi, and Ayutthaya were measured from December 22, 1998, to March 26, 1999, and from November 30, 1999, to December 2, 1999. Almost all the PM10 values in the high-polluted (H) area exceeded the Thailand National Ambient Air Quality Standards (NAAQS) of 120 microg/m3. The low-polluted (L) area showed low PM10 (34-74 microg/m3 in the daytime and 54-89 microg/m3 at night). PM2.5 in the H area varied between 82 and 143 microg/m3 in the daytime and between 45 and 146 microg/m3 at night. In the L area, PM2.5 was quite low both day and night and varied between 24 and 54 microg/m3, lower than the U.S. Environmental Protection Agency (EPA) standard (65 microg/m3). The personal exposure results showed a significantly higher proportion of PM2.5 to PM10 in the H area than in the L area (H = 0.80 +/- 0.08 and L = 0.65 +/- 0.04). Roadside PM10 was measured simultaneously with the Thailand Pollution Control Department (PCD) monitoring station at the same site and at the intersections where police work. The result from dual simultaneous measurements of PM10 showed a good correlation (correlation coefficient: r = 0.93); however, PM levels near the roadside at the intersections were higher than the concentrations at the monitoring station. The relationship between ambient PM level and actual personal exposures was examined. Correlation coefficients between the general ambient outdoors and personal exposure levels were 0.92 for both PM2.5 and PM10. Bangkok air quality data for 1997-2000, including 24-hr average PM10, NO2, SO2, and O3 from eight PCD monitoring stations, were analyzed and validated. The annual arithmetic mean PM10 of the PCD data at the roadside monitoring stations for the last 3 years decreased from 130 to 73 microg/m3, whereas the corresponding levels at the general monitoring stations decreased from 90 to 49 microg/m3. The proportion of days when the level of the 24-hr average PM10 exceeded the NAAQS was between 13 and 26% at roadside stations. PCD data showed PM10 was well correlated with NO2 but not with SO2, suggesting that automobile exhaust is the main source of the particulate air pollution. The results obtained from the simultaneous measurement of PM2.5 and PM10 indicate the potential environmental health hazard of fine particles. In conclusion, Bangkok traffic police were exposed to high levels of automobile-derived particulate air pollution.     

Application of a microscale emission factor model for particulate matter to calculate vehicle-generated contributions to fine particulate emissions

This paper discusses the evaluation and application of a new generation of particulate matter (PM) emission factor model (MicroFacPM). MicroFacPM that was evaluated in Tuscarora Mountain Tunnel, Pennsylvania Turnpike, PA shows good agreement between measured and modeled emissions. MicroFacPM application is presented to the vehicle traffic on the main approach road to the Ambassador Bridge, which is one of the most important international border entry points in North America, connecting Detroit, MI, with Windsor, Ontario, Canada. An increase in border security has forced heavy-duty diesel vehicles to line up for several kilometers through the city of Windsor causing concern about elevated concentrations of ambient PM. MicroFacPM has been developed to model vehicle-generated PM (fine [PM2.5] and coarse < or = 10 microm [PM10]) from the on-road vehicle fleet, which in this case includes traffic at very low speeds (10 km/h). The Windsor case study gives vehicle generated PM2.5 sources and their breakdown by vehicle age and class. It shows that the primary sources of vehicle-generated PM2.5 emissions are the late-model heavy-duty diesel vehicles. We also applied CALINE4 and AERMOD in conjunction with MicroFacPM, using Canadian traffic and climate conditions, to describe the vehicle-generated PM2.5 dispersion near this roadway during the month of May in 2003.     

Inflammatory effects of particulate matter air pollution

Environmental Science and Pollution Research - Air pollution is an important cause of non-communicable diseases globally with particulate matter (PM) as one of the main air pollutants. PM is...     

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.     

Characterisation of particulate exposure during fireworks displays

Little is known about the level and content of exposure to fine particles (PM_2.5) among persons who attend fireworks displays and those who live nearby. An evaluation of the levels of PM_2.5 and their elemental content was carried out during the nine launches of the 2007 Montréal International Fireworks Competition. For each event, a prediction of the location of the firework plume was obtained from the Canadian Meteorological Centre (CMC) of the Meteorological Service of Canada. PM_2.5 was measured continuously with a photometer (Sidepak?, TSI) within the predicted plume location (“predicted sites”), and integrated samples were collected using portable personal samplers. An additional sampler was located on a nearby roof (“fixed site”). The elemental composition of the collected PM_2.5 samples from the “predicted sites” was determined using both a non-destructive energy dispersive ED-XRF method and an ICP-MS method with a near-total microwave-assisted acid digestion. The elemental composition of the “fixed site” samples was determined by the ICP-MS with the near-total digestion method. The highest PM_2.5 levels reached nearly 10 000 μg m^?3, roughly 1000 times background levels. Elements such as K, Cl, Al, Mg and Ti were markedly higher in plume-exposed filters. This study shows that 1) persons in the plume and in close proximity to the launch site may be exposed to extremely high levels of PM_2.5 for the duration of the display and, 2) that the plume contains specific elements for which little is known of their acute cardio-respiratory toxicity.     

Particle size distribution predicts particulate phosphorus removal

Particulate phosphorus (PP) is often the largest component of the total phosphorus (P) load in stormwater. Fine-resolution measurement of particle sizes allows us to investigate the mechanisms behind the removal of PP in stormwater wetlands, since the diameter of particles influences the settling velocity and the amount of sorbed P on a particle. In this paper, we present a novel method to estimate PP, where we measure and count individual particles in stormwater and use the total surface area as a proxy for PP. Our results show a strong relationship between total particle surface area and PP, which we use to put forth a simple mechanistic model of PP removal via gravitational settling of individual mineral particles, based on a continuous particle size distribution. This information can help improve the design of stormwater Best management practices to reduce PP loading in both urban and agricultural watersheds.     

Driver exposure to particulate matter in Bangkok

The aims of this study were to determine the particulate matter with aerodynamic diameters > or = 2.5 microm (PM2.5) and 2.5-10 microm (PM10-2.5) exposure levels of drivers and to analyze the proportion of elemental carbon (EC) and organic carbon (OC) in PM2.5 in Bangkok, Thailand. Four bus routes were selected. Measurements were conducted over 10 days in August (rainy season) 2008 and 8 days in January (dry season) 2009. The mean PM2.5 exposure level of the Tuk-tuk drivers was 86 microg/m3 in August and 198 microg/m3 in January. The mean for the non-air-conditioned bus drivers was 63 microg/m3 in August and 125 microg/m3 in January. The PM2.5 and PM10-2.5 exposure levels of the drivers in January were approximately twice as high as those in August. The proportion of total carbon (TC) in PM2.5 to the PM2.5 level in August (0.97 +/- 0.28 microg/m3) was higher than in January (0.65 +/- 0.13 microg/m3). The proportion of OC in the TC of the PM2.5 in August (0.51 +/- 0.08 microg/m3) was similar to that in January (0.65 +/- 0.07 microg/m3). The TC exposure by PM25 in January (81 +/- 30 microg/m3) remained higher than in August (56-21 microg/m3). The mean level of OC in the PM2.5 was 29 +/- 13 microg/m3 in August and 50 +/- 24 microg/m3 in January. In conclusion, the PM exposure level in Bangkok drivers was higher than that in the general environment, which was already high, and it varied with the seasons and vehicle type. This study also demonstrated that the major component of the PM was carbon, likely derived from vehicles.     

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.     

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.     

Comparison of measured total suspended particulate matter concentrations using tapered element oscillating microbalance and a total suspended particulate sampler

A comparison of the concentration of the total suspended particulate (TSP) matter measured by the tapered element oscillating microbalance (TEOM) monitor and the isokinetic TSP samplers developed at the University of Illinois was carried out in several types of confinement livestock buildings. In a majority of the measurements done, the dust concentration measured by the TEOM monitor was lower than the University of Illinois at Urbana-Champaign (UIUC) isokinetic TSP sampler; the TEOM monitor tended to underestimate the total dust concentration by as much as 54%. The difference in measurements can be attributed to the sampling efficiency of the TEOM monitor sampling head and the loss of some semivolatile compounds and particle-bound water because of heating of the TEOM monitor sampling stream to 50 degrees C. Although several articles in the literature supported the latter argument, this study did not investigate the effect of heating the sampling stream or the effect of moisture on the relative difference in dust concentration measurements. The model that best describes the relationship between the two methods was site specific, that is, the linear regression model was applicable only to four of the sites monitored. The measured total dust concentration in livestock buildings range from approximately 300 to 4000 microg/m3; a higher correlation coefficient between TEOM-TSP and UIUC-TSP monitors was obtained in swine facilities than those obtained in a laying facility.     

柴油机微粒捕集器臭氧再生法离线再生

由R175型柴油机、微粒捕集器(Φ90 mm×150 mm)、CF-G10型臭氧发生器组成实验系统,进行了臭氧再生法离线再生研究。研究表明,在190℃温度下,再生气从DPF上游侧进气再生时,臭氧可以有效再生DPF,再生效率可达90%以上,再生效率达到65%左右时发生臭氧穿透,臭氧利用率下降;穿透时间点随微粒捕集时的柴油机载荷增大而提前,随微粒捕集时间增加而提前;臭氧供给量不变,再生气流量越大,再生效果越明显;再生气从DPF下游侧进气再生时,臭氧穿透时间点较上游侧进气再生滞后,但发生穿透后DPF几乎不再再生,总再生效率低于70%。结果表明,微粒捕集器臭氧再生法是可行的,对于如何提高臭氧利用率需进一步研究。     

Determination of levoglucosan in atmospheric fine particulate matter

A microanalytical method suitable for the quantitative determination of the sugar anhydride levoglucosan in low-volume samples of atmospheric fine particulate matter (PM) has been developed and validated. The method incorporates two sugar anhydrides as quality control standards. The recovery standard sedoheptulosan (2,7-anhydro-beta-D-altro-heptulopyranose) in 20 microL solvent is added onto samples of the atmospheric fine PM and aged for 1 hr before ultrasonic extraction with ethylacetate/ triethylamine. The extract is reduced in volume, an internal standard is added (1,5-anhydro-D-mannitol), and a portion of the extract is derivatized with 10% by volume N-trimethylsilylimidazole. The derivatized extract is analyzed by gas chromatography/mass spectrometry (GC/MS). The recovery of levoglucosan using this procedure was 69 +/- 6% from five filters amended with 2 microg levoglucosan, and the reproducibility of the assay is 9%. The limit of detection is approximately 0.1 microg/mL, which is equivalent to approximately 3.5 ng/m3 for a 10 L/min sampler or approximately 8.7 ng/m3 for a 4 L/min personal sampler (assuming 24-hr integrated samples). We demonstrated that levoglucosan concentrations in collocated samples (expressed as ng/m3) were identical irrespective of whether samples were collected by PM with aerodynamic diameter < or = 2.5 microm or PM with aerodynamic diameter < or = 10 microm impactors. It was also demonstrated that X-ray fluorescence analysis of samples of atmospheric PM, before levoglucosan determinations, did not alter the levels of levoglucosan.