Observations and Interpretations from the Canadian Fine Particle Monitoring Program

ABSTRACT

Canadian particle monitoring programs examining PM10, PM2.5, and particle composition have been in operation for over 10 years. Until recently, the measurements were manual/filter-based with 24-hr sample collection varying in frequency from daily to every sixth day, using GrasebyAnderson dichotomous samplers. In the past few years, these monitoring activities have been expanded to include hourly measurements using tapered element oscillating microbalances (TEOMs). This continuous monitoring program started operation focusing on PM_10, but now emphasizes PM_2.5 through the addition of more TEOMs and switching of the inlets of some of the existing units. The data from all of these measurement activities show that there are broad geographical differences and also local- to regional-scale spatial differences in mass and composition of PM2.5. Due to variations in sources, significantly different PM2.5 concentrations are not uncommon within the same city. Comparison of nearby urban and rural sites indicates that 30 and 40% of the PM_2.5 is from local urban sources in Montreal and Toronto, respectively. Hourly PM_2.5 measurements in Toronto suggest that vehicular emissions are an important contributor to urban PM_2.5. There has been a decreasing trend in urban PM_2.5, with annual average concentrations between the 1987–1990 and 1993–1995 periods decreasing by 11 to 39%, depending upon the site. The largest declines were in Montreal and Halifax, and the smallest decline was in Toronto. Comparison of 24-hr TEOM and manual dichotomous sampler PM_2.5 measurements from a site in Toronto indicates that the TEOM results in lower concentrations. The magnitude of this difference is relatively small in the warmer months, averaging about 12%. During the colder months the difference averages about 23%, but can be as large as 50%.     

Particulate Matter in California: Part 1—Intercomparison of Several PM2.5, PM10–2.5, and PM10 Monitoring Networks

Abstract

It will be many years before the recently deployed network of fine particulate matter with an aerodynamic diameter less than 2.5 [H9262]m (PM_2.5) Federal Reference Method (FRM) samplers produces information on nonattainment areas, trends, and source impacts. However, data on PM_2.5 and its major constituents have been routinely collected in California for the past 20 years. The California Air Resources Board operated as many as 20 dichotomous (dichot) samplers for PM_2.5 and coarse PM (PM_10–2.5). The California Acid Deposition Monitoring Program (CADMP) collected 12-h-average PM_2.5 and PM₁₀ from 1988 to 1995 at ten urban and rural sites and 24-h-average PM_2.5 at five urban sites since 1995. Beginning in 1994, the Children’s Health Study collected 2-week averages of PM_2.5 in 12 communities in southern California using the Two-Week Sampler (TWS). Comparisons of collocated samples establish relationships between the dichot, CADMP, and TWS samplers and the 82-site network of PM_2.5 FRM samplers deployed since 1999 in California. PM mass data from the different monitoring programs have modest to high correlation to FRM mass data, fairly small systematic biases and negative proportional biases ranging from 7 to 22%. If the biases are taken into account, all of the programs should be considered comparable with the FRM program. Thus, historical data can be used to develop long-term PM trends in California.     

Development of a Sample Equilibration System for the TEOM Continuous PM Monitor

ABSTRACT

In recent years, scientific discussion has included the influence of thermodynamic conditions (e.g., temperature, relative humidity, and filter face velocity) on PM retention efficiency of filter-based samplers and monitors. Method-associated thermodynamic conditions can, in some instances, dramatically influence the presence of particle-bound water and other light-molecular-weight chemical components such as particulate nitrates and certain organic compounds. The measurement of fine particle mass presents a new challenge for all PM measurement methods, since a relatively greater fraction of the mass is semi-volatile.

The tapered element oscillating microbalance (TEOM) continuous PM monitor is a U.S. Environmental Protection Agency (EPA) PM₁₀ equivalent method (EQPM-1090-079). Several hundred of these monitors are deployed throughout the United States. The TEOM monitor has the unique characteristic of providing direct PM mass measurement without the calibration uncertainty inherent in mass surrogate methods. In addition, it provides high-precision, near-real-time continuous data automatically. Much attention has been given to semi-volatile species retention of the TEOM method.

While using this monitor, it is desirable to maintain as low an operating temperature as practical and to remove unwanted particle-bound water. A new sample equilibration system (SES) has been developed to allow conditioning of the PM sample stream to a lower humidity and temperature level. The SES incorporates a special low-particle-loss Nafion dryer. This paper discusses the configuration and theory of the SES. Performance results include high time-resolved PM_2.5 data comparison between a 30 °C sample stream TEOM monitor with SES and a standard 50 °C TEOM monitor. In addition, 24-hr integrated data are compared with data collected using an EPA PM_2.5 Federal Reference Method (FRM)-type sampler. The SES is a significant development because it can be applied easily to existing TEOM monitors.     

Collocated comparisons of continuous and filter-based PM2.5 measurements at Fort McMurray,Alberta, Canada

Collocated comparisons for three PM_2.5 monitors were conducted from June 2011 to May 2013 at an air monitoring station in the residential area of Fort McMurray, Alberta, Canada, a city located in the Athabasca Oil Sands Region. Extremely cold winters (down to approximately ?40°C) coupled with low PM_2.5 concentrations present a challenge for continuous measurements. Both the tapered element oscillating microbalance (TEOM), operated at 40°C (i.e., TEOM₄₀), and Synchronized Hybrid Ambient Real-time Particulate (SHARP, a Federal Equivalent Method [FEM]), were compared with a Partisol PM_2.5 U.S. Federal Reference Method (FRM) sampler. While hourly TEOM₄₀ PM_2.5 were consistently ~20–50% lower than that of SHARP, no statistically significant differences were found between the 24-hr averages for FRM and SHARP. Orthogonal regression (OR) equations derived from FRM and TEOM₄₀ were used to adjust the TEOM₄₀ (i.e., TEOM_adj) and improve its agreement with FRM, particularly for the cold season. The 12-year-long hourly TEOM_adj measurements from 1999 to 2011 based on the OR equations between SHARP and TEOM₄₀ were derived from the 2-year (2011–2013) collocated measurements. The trend analysis combining both TEOM_adj and SHARP measurements showed a statistically significant decrease in PM_2.5 concentrations with a seasonal slope of ?0.15 μg m^?3 yr^?1 from 1999 to 2014.Implications: Consistency in PM_2.5 measurements are needed for trend analysis. Collocated comparison among the three PM_2.5 monitors demonstrated the difference between FRM and TEOM, as well as between SHARP and TEOM. The orthogonal regressions equations can be applied to correct historical TEOM data to examine long-term trends within the network.     

Analysis of PM10 Trends in the United States from 1988 through 1995

ABSTRACT

Because the U. S. Environmental Protection Agency (EPA) has changed the National Ambient Air Quality Standards (NAAQS) for ambient particulate matter (PM), there is a great deal of interest in determining recent PM trends. This paper examines trends in PM₁₀ (i.e., particulate matter less than 10 micrometers in diameter) for areas of the United States based on their attainment status—for PM₁₀ and ozone nonattainment and attainment areas. The analysis also focuses on urban, suburban, and rural areas, and eastern and western areas. The time period of evaluation is from 1988 through 1995. To shed further light on the ambient PM₁₀ trends, trends in ambient SO₂, NO₂, and volatile organic compounds (VOCs) are also analyzed. Finally, trends in emission inventories of SO₂, NO_x, VOCs, and PM₁₀ are evaluated. Results of the analysis show that widespread and similar reductions in PM₁₀ levels have occurred over the last seven years. Annual reductions range from 3.0% to 3.8%, with the greatest reductions coming in PM₁₀ nonattainment areas, but with very significant reductions also in PM₁₀ attainment areas, ozone attainment areas, and rural areas. The widespread reductions appear to be due to a set of controls or common factors that are having a fairly uniform effect in all of the areas. The consistency of the reductions in different areas suggests that the reductions may also be primarily in the fine particles (i.e., those less than 2.5 micrometers in diameter, or PM_2.5), which are more readily transported than coarse particles.     

Application of positive matrix factorization in characterization of PM(10) and PM(2.5) emission sources at urban roadside

The 24-h average coarse (PM₁₀) and fine (PM_2.5) fraction of airborne particulate matter (PM) samples were collected for winter, summer and monsoon seasons during November 2008-April 2009 at an busy roadside in Chennai city, India. Results showed that the 24-h average ambient PM₁₀ and PM_2.5 concentrations were significantly higher in winter and monsoon seasons than in summer season. The 24-h average PM₁₀ concentration of weekdays was significantly higher (12-30%) than weekends of winter and monsoon seasons. On weekends, the PM_2.5 concentration was found to slightly higher (4-15%) in monsoon and summer seasons. The chemical composition of PM₁₀ and PM_2.5 masses showed a high concentration in winter followed by monsoon and summer seasons.The U.S.EPA-PMF (positive matrix factorization) version 3 was applied to identify the source contribution of ambient PM₁₀ and PM_2.5 concentrations at the study area. Results indicated that marine aerosol (40.4% in PM₁₀ and 21.5% in PM_2.5) and secondary PM (22.9% in PM₁₀ and 42.1% in PM_2.5) were found to be the major source contributors at the study site followed by the motor vehicles (16% in PM₁₀ and 6% in PM_2.5), biomass burning (0.7% in PM₁₀ and 14% in PM_2.5), tire and brake wear (4.1% in PM₁₀ and 5.4% in PM_2.5), soil (3.4% in PM₁₀ and 4.3% in PM_2.5) and other sources (12.7% in PM₁₀ and 6.8% in PM_2.5).     

Development and Evaluation of a Continuous Coarse (PM10–PM25) Particle Monitor

ABSTRACT

In this paper, we describe the development and laboratory and field evaluation of a continuous coarse (2.5-10 um) particle mass (PM) monitor that can provide reliable measurements of the coarse mass (CM) concentrations in time intervals as short as 5-10 min. The operating principle of the monitor is based on enriching CM concentrations by a factor of ~25 by means of a 2.5-um cut point round nozzle virtual impactor while maintaining fine mass (FM)—that is, the mass of PM_{2 5} at ambient concentrations. The aerosol mixture is subsequently drawn through a standard tapered element oscillating microbalance (TEOM), the response of which is dominated by the contributions of the CM, due to concentration enrichment. Findings from the field study ascertain that a TEOM coupled with a PM₁₀ inlet followed by a 2.5-um cut point round nozzle virtual impactor can be used successfully for continuous CM concentration measurements. The average concentration-enriched CM concentrations measured by the TEOM were 26-27 times higher than those measured by the time-integrated PM₁₀ samplers [the micro-orifice uniform deposit     

Errors in coarse particulate matter mass concentrations and spatiotemporal characteristics when using subtraction estimation methods

In studies of coarse particulate matter (PM_10-2.5), mass concentrations are often estimated through the subtraction of PM_2.5 from collocated PM₁₀ tapered element oscillating microbalance (TEOM) measurements. Though all field instruments have yet to be updated, the Filter Dynamic Measurement System (FDMS) was introduced to account for the loss of semivolatile material from heated TEOM filters. To assess errors in PM_10-2.5 estimation when using the possible combinations of PM₁₀ and PM_2.5 TEOM units with and without FDMS, data from three monitoring sites of the Colorado Coarse Rural–Urban Sources and Health (CCRUSH) study were used to simulate four possible subtraction methods for estimating PM_10-2.5 mass concentrations. Assuming all mass is accounted for using collocated TEOMs with FDMS, the three other subtraction methods were assessed for biases in absolute mass concentration, temporal variability, spatial correlation, and homogeneity. Results show collocated units without FDMS closely estimate actual PM_10-2.5 mass and spatial characteristics due to the very low semivolatile PM_10-2.5 concentrations in Colorado. Estimation using either a PM_2.5 or PM₁₀ monitor without FDMS introduced absolute biases of 2.4 µg/m³ (25%) to –2.3 µg/m³ (–24%), respectively. Such errors are directly related to the unmeasured semivolatile mass and alter measures of spatiotemporal variability and homogeneity, all of which have implications for the regulatory and epidemiology communities concerned about PM_10-2.5. Two monitoring sites operated by the state of Colorado were considered for inclusion in the CCRUSH acute health effects study, but concentrations were biased due to sampling with an FDMS-equipped PM_2.5 TEOM and PM₁₀ TEOM not corrected for semivolatile mass loss. A regression-based model was developed for removing the error in these measurements by estimating the semivolatile concentration of PM_2.5 from total PM_2.5 concentrations. By estimating nonvolatile PM_2.5 concentrations from this relationship, PM_10-2.5 was calculated as the difference between nonvolatile PM₁₀ and PM_2.5 concentrations.

Implications: Errors in the estimation of PM_10-2.5 concentrations using subtraction methods were shown to be related to the unmeasured semivolatile mass when using certain combinations of TEOM instruments. For the northeastern Colorado region, the absolute bias associated with this error significantly affects mean and 95th percentile values, which would affect assessment of compliance if PM_10-2.5 is regulated in the future. Estimating PM_10-2.5 mass concentrations using nonvolatile mass concentrations from collocated PM₁₀ and PM_2.5 TEOM monitors closely estimates the total PM_10-2.5 mass concentrations. A corrective model that removes the described error was developed and applied to data from two sites in Denver.

Supplemental Materials: Supplemental materials are available for this paper. Go to the publisher's online edition of the Journal of the Air & Waste Management Association.     

Techniques for High-Quality Ambient Coarse Particle Mass Measurements

ABSTRACT

Several recent studies have shown associations between ambient concentrations of particle mass (PM) and rates of morbidity and mortality in the general population. These studies have raised the issue of quality of coarse mass (CM, PM between 2.5 and 10 µm) data used for these purposes. CM data may have precision three or more times worse than the associated PM _2.5 or PM₁₀ data, depending on the measurement method, PM _2.5 to PM ₁₀ ratios, and CM concentrations. CM is measured either as the difference between collocated _PM10 and _PM2.5 samplers or more directly with a dichotomous (virtual impactor) sampler. CM precision for the difference method is degraded due to the increased errors inherent with using the difference between two independent measurements, as well as the high PM_2.5 to PM₁₀ ratios (and low CM concentrations) typical of the eastern United States. The dichotomous sampler (dichot) makes a more direct measurement of CM, but there is a potential for significant postexposure loss of particles from unoiled CM dichot filters, as well as uncertainties in the dichot’s CM channel enrichment factor. Compared to the dichot, low-volume inertial impactor samplers such as the Harvard Impactor (HI) or PM2.5 Federal Reference Method (FRM) are simpler to operate and maintain, provide sharper cut points, and do not require oiled filters to prevent loss of CM from the filter during transport. With the recent interest in CM spatial and temporal variability with respect to PM health effects, we have developed modifications to the HI PM method to provide measurements of 24-hour PM with estimated CM precision of better than 5% CV and r² higher than 0.95, primarily by lowering field blank variability and increasing gravimetric analytical precision. These high-precision PM techniques are not limited to the HI sampler; they can also be applied to the _PM2.5 FRM sampler. The measurement methods described here can be applied to future PM studies to avoid the potential problems with exposure assessment caused by CM measurements that have poor precision.     

Development of a PM2 5 Emissions Inventory for the South Coast Air Basin

ABSTRACT

With the promulgation of a national PM_2.5 ambient air quality standard, it is important that PM_2.5 emissions inventories be developed as a tool for understanding the magnitude of potential PM2.5 violations. Current PM₁₀ inventories include only emissions of primary particulate matter (1 ^ï PM), whereas, based on ambient measurements, both PM₁₀ and PM2.5 emissions inventories will need to include sources of both 1^ï PM and secondary particulate matter (2^ï PM). Furthermore, the U. S. Environmental Protection Agency’s (EPA) current edition of AP-42 includes size distribution data for 1o PM that overestimate the PM_2.5 fraction of fugitive dust sources by at least a factor of 2 based on recent studies.

This paper presents a PM_2.5 emissions inventory developed for the South Coast Air Basin (SCAB) that for the first time includes both 1^ï PM and 2^ï PM. The former is calculated by multiplying PM₁₀ emissions estimates by the PM_2.5/PM₁₀ ratios for different sources. The latter is calculated from estimated emission rates of gas-phase aerosol precursor and gas to aerosol conversion rates consistent with the measured chemical composition of ambient PM_2.5 concentrations observed in the SCAB. The major finding of this PM_2.5 emissions inventory is that the ^2ï aerosol component is more than twice the ^1ï aerosol component, which may result in widely different control strategies being required for fine PM and coarse PM.     

New York State urban and rural measurements of continuous PM2.5 mass by FDMS, TEOM, and BAM

Field evaluations and comparisons of continuous fine particulate matter (PM2,5) mass measurement technologies at an urban and a rural site in New York state are performed. The continuous measurement technologies include the filter dynamics measurement system (FDMS) tapered element oscillating microbalance (TEOM) monitor, the stand-alone TEOM monitor (without the FDMS), and the beta attenuation monitor (BAM). These continuous measurement methods are also compared with 24-hr integrated filters collected and analyzed under the Federal Reference Method (FRM) protocol. The measurement sites are New York City (the borough of Queens) and Addison, a rural area of southwestern New York state. New York City data comparisons between the FDMS TEOM, BAM, and FRM are examined for bias and seasonality during a 2-yr period. Data comparisons for the FDMS TEOM and FRM from the Addison location are examined for the same 2-yr period. The BAM and FDMS measurements at Queens are highly correlated with each other and the FRM. The BAM and FDMS are very similar to each other in magnitude, and both are approximately 25% higher than the FRM filter measurements at this site. The FDMS at Addison measures approximately 9% more mass than the FRM. Mass reconstructions using the speciation trends network filter data are examined to provide insight as to the contribution of volatile species of PM2.5 in the FDMS mass measurement and the fraction that is likely lost in the FRM mass measurement. The reconstructed mass at Queens is systematically lower than the FDMS by approximately 10%.     

Particulate Matter in California: Part 2—Spatial,Temporal, and Compositional Patterns of PM2.5, PM10–2.5, and PM10

Abstract

Geographic and temporal variations in the concentration and composition of particulate matter (PM) provide important insights into particle sources, atmospheric processes that influence particle formation, and PM management strategies. In the nonurban areas of California, annual-average PM_2.5 and PM₁₀ concentrations range from 3 to 10 [H9262]g/m³ and from 5 to 18 µg/m³, respectively. In the urban areas of California, annual-averages for PM_2.5 range from 7 to 30 [H9262]g/m³, with observed 24-hr peaks reaching levels as high as 160 [H9262]g/m³. Within each air basin, exceedances are a mixture of isolated events as well as periods of elevated PM_2.5 concentrations that are more prolonged and regional in nature. PM_2.5 concentrations are generally highest during the winter months. The exception is the South Coast Air Basin, where fairly high values occur throughout the year. Annual-average PM_2.5 mass, as well as the concentrations of major components, declined from 1988 to 2000. The declines are especially pronounced for the sulfate (SO₄ ^2?) and nitrate (NO₃ ^?) components of PM_2.5 and PM₁₀ and correlate with reductions in ambient levels of oxides of sulfur (SO_x) and oxides of nitrogen (NO_x). Annual averages for PM_10–2.5 and PM₁₀ exhibited similar downwind trends from 1994 to 1999, with a slightly less pronounced decrease in the coarse fraction.     

Characterization of Particulate Matter in California

ABSTRACT

The size, composition, and concentration of particulate matter (PM) vary with location and time. Several monitoring/sampling programs are operated in California to characterize PM less than 2.5 and 10 µm in aerodynamic diameter (PM_2.5 and PM₁₀). This paper presents a broad summary of the spatial and temporal variations observed in ambient PM_2.5 and PM₁₀ concentrations in California. Many areas that have high PM₁₀ concentrations also have relatively high PM_2.5 concentrations, and data indicate that a significant portion of the PM₁₀ air quality problem is caused by PM_2.5. To develop effective plans for attaining the ambient PM standards, improved understanding of these unique problems is needed. Since 1989, pollution control efforts—whether specifically targeted for particulate matter or indirectly via controls on gaseous emissions—have caused annual average PM_2.5 and PM₁₀ concentrations to decline at most sites in California.     

Wintertime PM2.5 and PM10 Source Apportionment at Sacramento,California

ABSTRACT

The chemical mass balance (CMB) model was applied to winter (November through January) 1991–1996 PM2.5 and PM10 data from the Sacramento 13th and T Streets site in order to identify the contributions from major source categories to peak 24-hr ambient PM_2.5 and PM₁₀ levels. The average monthly PM₁₀ monitoring data for the nine-year period in Sacramento County indicate that elevated concentrations are typical in the winter months. Concentrations on days of highest PM₁₀ are dominated by the PM2.5 fraction. One factor contributing to increased PM_2.5 concentrations in the winter is meteorology (cool temperatures, low wind speeds, low inversion layers, and more humid conditions) that favors the formation of secondary nitrate and sulfate aerosols. Residential wood burning also elevates fine particulate concentrations in the Sacramento area.

The results of the CMB analysis highlight three key points. First, the source apportionment results indicate that primary motor vehicle exhaust and wood smoke are significant sources of both PM_2.5 and PM₁₀ in winter. Second, nitrates, secondarily formed as a result of motor-vehicle and other sources of nitrogen oxide (NO_x), are another principal cause of the high PM_2.5 and PM₁₀ levels during the winter months. Third, fugitive dust, whether it is resuspended soil and dust or agricultural tillage, is not the major contributor to peak winter PM_2.5 and PM10 levels in the Sacramento area.     

Fine Particulate Matter Emissions Inventories: Comparisons of Emissions Estimates with Observations from Recent Field Programs

Abstract

Emissions inventories of fine particulate matter (PM_2.5) were compared with estimates of emissions based on data emerging from U.S. Environment Protection Agency Particulate Matter Supersites and other field programs. Six source categories for PM_2.5 emissions were reviewed: on-road mobile sources, nonroad mobile sources, cooking, biomass combustion, fugitive dust, and stationary sources. Ammonia emissions from all of the source categories were also examined. Regional emissions inventories of PM in the exhaust from on-road and nonroad sources were generally consistent with ambient observations, though uncertainties in some emission factors were twice as large as the emission factors. In contrast, emissions inventories of road dust were up to an order of magnitude larger than ambient observations, and estimated brake wear and tire dust emissions were half as large as ambient observations in urban areas. Although comprehensive nationwide emissions inventories of PM_2.5 from cooking sources and biomass burning are not yet available, observational data in urban areas suggest that cooking sources account for approximately 5–20% of total primary emissions (excluding dust), and biomass burning sources are highly dependent on region. Finally, relatively few observational data were available to assess the accuracy of emission estimates for stationary sources. Overall, the uncertainties in primary emissions for PM_2.5 are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM_2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods.     

Long-Term Field Characterization of Tapered Element Oscillating Microbalance and Modified Tapered Element Oscillating Microbalance Samplers in Urban and Rural New York State Locations

Abstract

Long-term field comparisons of continuous and integrated filter measurements of mass concentrations of par-ticulate matter (PM) with an aerodynamic diameter less than or equal to 2.5 μm (PM_2.5) were performed at rural and urban sites in New York State. Two versions of the continuous tapered element oscillating microbalance (TEOM) mass monitor are deployed at each site, in addition to Federal Reference Method filter samplers. Data are grouped into monthly averages to retain and demonstrate seasonal differences. Strong seasonal dependence is observed—the TEOM monitors with the heated sensors are biased systematically low with respect to the Federal Reference Method measurements during the cold season. For the rural site, the average bias for the sample equilibration system (SES)-equipped and standard TEOM monitors is 14 and 24%, respectively. At this location, the TEOM monitor measurements were biased low for all 34 months. For the urban site, the average bias for the SES and standard TEOM monitors is 8 and 18%, respectively. At this location, the TEOM monitor measurements are as likely to be biased high as low during the warm-season months. The hour averaged data from the two versions of the TEOM monitor are also compared, and also indicate that the SES-equipped version of the TEOM monitor captures 7-11% more PM_2.5 mass at these locations.     

Effects of Equilibration Temperature on PM10 Concentrations from the TEOM Method in the Lower Fraser Valley

ABSTRACT

This study investigated the effect of equilibration temperature on PM₁₀ concentrations from the tapered element oscillating microbalance (TEOM) method by operating collocated TEOM monitors at different equilibration temperatures in an airshed (the Lower Fraser Valley, British Columbia). This airshed contained an abundance of par-ticulate semivolatile material (PSVM). For the period when three collocated TEOM monitors were operated, the PM₁₀ from the monitor at an equilibration temperature of 30 ° C was 2.5 μ g/m³ (22%) and 1.7 (17%) μ g/m³ higher, on average, than the PM₁₀ from monitors at 50 and 40 ° C, respectively, and the differences were proportional to the ambient PM₁₀ loading. Greater volatilization of PSVM in the TEOM monitors at higher equilibration temperatures may have been a cause of the differences.     

Field performance of dichotomous sequential PM air samplers

For over one year, the Environmental Protection Commission of Hillsborough County (EPCHC) in Tampa, Florida, operated two dichotomous sequential particulate matter air samplers collocated with a manual Federal Reference Method (FRM) air sampler at a waterfront site on Tampa Bay. The FRM was alternately configured as a PM_2.5, then as a PM₁₀ sampler. For the dichotomous sampler measurements, daily 24-h integrated PM_2.5 and PM_10–2.5 ambient air samples were collected at a total flow rate of 16.7 l min⁻¹. A virtual impactor split the air into flow rates of 1.67 and 15.0 l min⁻¹ onto PM_10–2.5 and PM_2.5 47-mm diameter PTFE^® filters, respectively. Between the two dichotomous air samplers, the average concentration, relative bias and relative precision were 13.3 μg m⁻³, 0.02% and 5.2% for PM_2.5 concentrations (n=282), and 12.3 μg m⁻³, 3.9% and 7.7% for PM_10–2.5 concentrations (n=282). FRM measurements were alternate day 24-h integrated PM_2.5 or PM₁₀ ambient air samples collected onto 47-mm diameter PTFE^® filters at a flow rate of 16.7 l min⁻¹. Between a dichotomous and a PM_2.5 FRM air sampler, the average concentration, relative bias and relative precision were 12.4 μg m⁻³, −5.6% and 8.2% (n=43); and between a dichotomous and a PM₁₀ FRM air sampler, the average concentration, relative bias and relative precision were 25.7 μg m⁻³, −4.0% and 5.8% (n=102). The PM_2.5 concentration measurement standard errors were 0.95, 0.79 and 1.02 μg m⁻³; for PM₁₀ the standard errors were 1.06, 1.59, and 1.70 μg m⁻³ for two dichotomous and one FRM samplers, respectively, which indicate the dichotomous samplers have superior technical merit. These results reveal the potential for the dichotomous sequential air sampler to replace the combination of the PM_2.5 and PM₁₀ FRM air samplers, offering the capability of making simultaneous, self-consistent determinations of these particulate matter fractions in a routine ambient monitoring mode.     

Quantitative cancer risk assessment and local mortality burden for ambient air pollution in an eastern Mediterranean City

Health risks posed by ambient air pollutants to the urban Lebanese population have not been well characterized. The aim of this study is to assess cancer risk and mortality burden of non-methane hydrocarbons (NMHCs) and particulates (PM) based on two field-sampling campaigns conducted during summer and winter seasons in Beirut. Seventy NMHCs were analyzed by TD-GC-FID. PM_2.5 elemental carbon (EC) components were examined using a Lab OC-EC aerosol Analyzer, and polycyclic aromatic hydrocarbons were analyzed by GC-MS. The US EPA fraction-based approach was used to assess non-cancer hazard and cancer risk for the hydrocarbon mixture, and the UK Committee on Medical Effects of Air Pollutants (COMEAP) guidelines were followed to determine the PM_2.5 attributable mortality burden. The average cumulative cancer risk exceeded the US EPA acceptable level (10⁻⁶) by 40-fold in the summer and 30-fold in the winter. Benzene was found to be the highest contributor to cancer risk (39–43%), followed by 1,3-butadiene (25–29%), both originating from traffic gasoline evaporation and combustion. The EC attributable average mortality fraction was 7.8–10%, while the average attributable number of deaths (AD) and years of life lost (YLL) were found to be 257–327 and 3086–3923, respectively. Our findings provide a baseline for future air monitoring programs, and for interventions aiming at reducing cancer risk in this population.

     

Air quality at Santiago,Chile: a box modeling approach II. PM2.5, coarse and PM10 particulate matter fractions

Ambient monitored data at Santiago, Chile, are analyzed using box models with the goal of assessing contributions of different economic activities to air pollution levels. The box modeling approach was applied to PM₁₀, PM_2.5 and coarse (PM₁₀–PM_2.5) particulate matter (PM) fractions; the period analyzed is 1989–1999. A linear model for each PM fraction was obtained, having as independent variables CO and SO₂ concentrations, plus a term proportional to (wind speed)⁻¹ that lumps together non-combustion emissions and secondary generation terms; wet scavenging is included as another independent variable. Model identification results show good agreement for the different parameters across monitoring stations. The washout ratios and scavenging coefficients agree with data published in the literature, being higher for the coarse PM fraction. The CO and SO₂ coefficients fitted for 1989–1995 agree with a priori estimates for the same period. Background estimates for the PM fractions are in agreement with measurement campaigns in upwind sites. Results show that transportation sources have become the dominant contributors to ambient PM levels, while stationary sources have decreased their contributions in the last years. The relative importance of mobile sources to PM_2.5 ambient concentrations has doubled in the last 10 years, whereas stationary sources have reduced their relative contributions to half the value in the early 1990s. Model estimates of regional background of PM_2.5 and PM₁₀ have decreased 50% and 22% in the last decade, respectively; coarse background has shown no significant change. The final conclusion is that there is room and need for a more intensive emission reduction strategy for Santiago, focusing on mobile sources. The approach pursued in this work is feasible for cities or regions where comprehensive, transport and chemistry models are not available yet, but estimates of air quality contributions are needed for policy purposes. The methodology requires data on ambient air quality measurements and surface meteorology.