Laboratory and field evaluation of measurement methods for one-hour exposures to O3, PM2.5, and CO.

While researchers have linked acute (less than 12-hr) ambient O3, PM2.5, and CO concentrations to a variety of adverse health effects, few studies have characterized short-term exposures to these air pollutants, in part due to the lack of sensitive, accurate, and precise sampling technologies. In this paper, we present results from the laboratory and field evaluation of several new (or modified) samplers used in the "roll-around" system (RAS), which was developed to measure 1-hr O3, PM2.5, and CO exposures simultaneously. All the field evaluation data were collected during two sampling seasons: the summer of 1998 and the winter of 1999. To measure 1-hr O3 exposures, a new active O3 sampler was developed that uses two nitrite-coated filters to measure O3 concentrations. Laboratory chamber tests found that the active O3 sampler performed extremely well, with a collection efficiency of 0.96 that did not vary with temperature or relative humidity (RH). In field collocation comparisons with a reference UV photometric monitor, the active O3 sampler had an effective collection efficiency ranging between 0.92 and 0.96 and a precision for 1-hr measurements ranging between 4 and 6 parts per billion (ppb). The limits of detection (LOD) of this method were 9 ppb-hr for the chamber tests and approximtely 16 ppb-hr for the field comparison tests. PM2.5 and CO concentrations were measured using modified continuous monitors--the DustTrak and the Langan, respectively. A size-selective inlet and a Nafion dryer were placed upstream of the DustTrak inlet to remove particles with aerodynamic diameters greater than 2.5 microm and to dry particles prior to the measurements, respectively. During the field validation tests, the DustTrak consistently reported higher PM2.5 concentrations than those obtained by the collocated 12-hr PM2.5 PEM samples, by approximately a factor of 2. After the DustTrak response was corrected (correction factor of 2.07 in the summer and 2.02 in the winter), measurements obtained using these methods agreed well with R2 values of 0.87 in the summer and 0.81 in the winter. The results showed that the DustTrak can be used along with integrated measurements to measure the temporal and spatial variation in PM2.5 exposures. Finally, during the field validation tests, CO concentrations measured using the Langan were strongly correlated with those obtained using the reference method when the CO levels were above the LOD of the instrument [approximately 1 part per million (ppm)].     

Assessing the Relationship between Personal Particulate and Gaseous Exposures of Senior Citizens Living in Baltimore,MD

ABSTRACT

We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (>64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM₂₅, PM₁₀, SO₄ ^2-, O₃, NO₂, SO₂, and exhaust-related VOCs.

Results of this study showed that longitudinal associations between ambient PM_2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM_2.5 exposures and resulting personal-ambient associations. Associations between personal PM₂₅ exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM_{2 5} sources. Evidence for this was provided by SO₄ ^2-measurements, which can be thought of as a tracer for ambient PM₂₅. For SO₄ ^2-, personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM_2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM_2.5 sources to personal PM_2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments.

Results also indicate that the potential for confounding by PM_2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM_2.5 exposures were not significantly correlated with personal exposures to PM_2.5-10, PM_2.5 of non-ambient origin, O₃, NO₂, and SO₂. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM_2.5 epidemiologic studies are unlikely to be due to confounding by the PM_2.5 co-pollutants measured in this study.     

Filtration of Radioactive Aerosols By Glass Fibers

Abstract

An ozone (O₃) exposure assessment study was conducted in Toronto, Ontario, Canada during the winter and summer of 1992. A new passive O₃ sampler developed by Harvard was used to measure indoor, outdoor, and personal O₃ concentrations. Measurements were taken weekly and daily during the winter and summer, respectively. Indoor samples were collected at a total of 50 homes and workplaces of study participants. Outdoor O₃ concentrations were measured both at home sites using the passive sampler and at 20 ambient monitoring sites with continuous monitors. Personal O₃ measurements were collected from 123 participants, who also completed detailed time-activity diaries. A total of 2,274 O₃ samples were collected. In addition, weekly air exchange rates of homes were measured.

This study demonstrates the performance of our O₃ sampler for exposure assessment. The data obtained are further used to examine the relationships between personal, indoor (home and workplace), and outdoor O₃ concentrations, and to investigate outdoor and indoor spatial variations in O₃ concentrations. Based on home outdoor and indoor, workplace, and ambient O₃ concentrations measured at the Ontario Ministry of the Environment (MOE) sites, the traditional microenvironmental model predicts 72% of the variability in measured personal exposures. An alternative personal O₃ exposure model based on outdoor measurements and time-activity information is able to predict the mean personal exposures in a large population, with the highest R² value of 0.41.     

Major air pollutants in Bursa,Turkey: their levels,temporal changes,interactions, and sources

Bursa is one of the largest cities of Turkey and it hosts 17 organized industrial zones. Parallel to the increase in population, rapidly growing energy consumption, and increased numbers of transport vehicles have impacts on the air quality of the city. In this study, regularly calibrated automatic samplers were employed to get the levels of air pollution in Bursa. The concentrations of CH₄ and N-CH₄ as well as the major air pollutants including PM₁₀, PM_2.5, NO, NO₂, NO_x, SO₂, CO, and O₃, were determined for 2016 and 2017 calendar years. Their levels were 1641.62?±?718.25, 33.11?±?5.45, 42.10?±?10.09, 26.41?±?9.01, 19.47?±?16.51, 46.73?±?16.56, 66.23?±?32.265, 7.60?±?3.43, 659.397?±?192.73, and 51.92?±?25.63 µg/m³ for 2016, respectively. Except for O₃, seasonal concentrations were higher in winter and autumn for both years. O₃, CO, and SO₂ had never exceeded the limit values specified in the regulations yet PM₁₀, PM_2.5, and NO₂ had violated the limits in some days. The ratios of CO/NO_x, SO₂/NO_x, and PM_2.5/PM₁₀ were examined to characterize the emission sources. Generally, domestic and industrial emissions were dominated in the fall and winter seasons, yet traffic emissions were effective in spring and summer seasons. As a result of the correlation process between O_x and NO_x, it was concluded that the most important source of O_x concentrations in winter was NO_x and O₃ was in summer.     

Defining the Photochemical Contribution to Particulate Matter in Urban Areas Using Time-Series Analysis

Abstract

The objective of this project is to demonstrate how the ambient air measurement record can be used to define the relationship between O₃ (as a surrogate for photochemistry) and secondary particulate matter (PM) in urban air. The approach used is to develop a time-series transfer-function model describing the daily PM₁₀ (PM with less than 10 μm aerodynamic diameter) concentration as a function of lagged PM and current and lagged O₃, NO or NO₂, CO, and SO₂. Approximately 3 years of daily average PM₁₀, daily maximum 8-hr average O₃ and CO, daily 24-hr average SO₂ and NO₂, and daily 6:00 a.m.-9:00 a.m. average NO from the Aerometric Information Retrieval System (AIRS) air quality subsystem are used for this analysis. Urban areas modeled are Chicago, IL; Los Angeles, CA; Phoenix, AZ; Philadelphia, PA; Sacramento, CA; and Detroit, MI. Time-series analysis identified significant autocorrelation in the O₃, PM₁₀, NO, NO₂,CO, and SO₂ series. Cross correlations between PM₁₀ (dependent variable) and gaseous pollutants (independent variables) show that all of the gases are significantly correlated with PM₁₀ and that O₃ is also significantly correlated lagged up to two previous days. Once a transfer-function model of current PM₁₀ is defined for an urban location, the effect of an O₃-control strategy on PM concentrations is estimated by calculating daily PM₁₀ concentrations with reduced O₃ concentrations. Forecasted summertime PM₁₀ reductions resulting from a 5 percent decrease in ambient O₃ range from 1.2 μg/m³ (3.03%) in Chicago to 3.9 μg/m³ (7.65%) in Phoenix.     

The Aerosol Research and Inhalation Epidemiology Study (ARIES): PM25 Mass and Aerosol Component Concentrations and Sampler Intercomparisons

ABSTRACT

The Aerosol Research and Inhalation Epidemiology Study (ARIES) was designed to provide high-quality measurements of PM₂₅, its components, and co-varying pollutants for an air pollution epidemiology study in Atlanta, GA.

Air pollution epidemiology studies have typically relied on available data on particle mass often collected using filter-based methods. Filter-based PM_2.5 sampling is susceptible to both positive and negative errors in the measurement of aerosol mass and particle-phase component concentrations in the undisturbed atmosphere. These biases are introduced by collection of gas-phase aerosol components on the filter media or by volatilization of particle phase components from collected particles. As part of the ARIES, we collected daily 24-hr PM_2.5 mass and speciation samples and continuous PM_2.5 data at a mixed residential-light industrial site in Atlanta. These data facilitate analysis of the effects of a wide variety of factors on sampler performance. We assess the relative importance of PM_2.5 components and consider associations and potential mechanistic linkages of PM_2.5 mass concentrations with several PM_2.5 components.

For the 12 months of validated data collected to date (August 1, 1998-July 31, 1999), the monthly average Federal Reference Method (FRM) PM_{2 5} mass always exceeded the proposed annual average standard (12-month average = 20.3 ± 9.5 ug/m³). The particulate SO₄ ^2- fraction (as (NH₄)₂SO₄) was largest in the summer and exceeded 50% of the FRM mass. The contribution of (NH₄)₂SO₄ to FRM PM_2.5 mass dropped to less than 30% in winter. Particu-late NO₃ ^- collected on a denuded nylon filter averaged 1.1 ± 0.9 ug/m³. Particle-phase organic compounds (as organic carbon × 1.4) measured on a denuded quartz filter sampler averaged 6.4 ± 3.1 ug/m³ (32% of FRM PM_{2 5} mass) with less seasonal variability than SO₄ ^2-.     

Comparison of real-time instruments and gravimetric method when measuring particulate matter in a residential building

This study used several real-time and filter-based aerosol instruments to measure PM_2.5 levels in a high-rise residential green building in the Northeastern US and compared performance of those instruments. PM_2.5 24-hr average concentrations were determined using a Personal Modular Impactor (PMI) with 2.5 µm cut (SKC Inc., Eighty Four, PA) and a direct reading pDR-1500 (Thermo Scientific, Franklin, MA) as well as its filter. 1-hr average PM_2.5 concentrations were measured in the same apartments with an Aerotrak Optical Particle Counter (OPC) (model 8220, TSI, Inc., Shoreview, MN) and a DustTrak DRX mass monitor (model 8534, TSI, Inc., Shoreview, MN). OPC and DRX measurements were compared with concurrent 1-hr mass concentration from the pDR-1500. The pDR-1500 direct reading showed approximately 40% higher particle mass concentration compared to its own filter (n = 41), and 25% higher PM_2.5 mass concentration compared to the PMI_2.5 filter. The pDR-1500 direct reading and PMI_2.5 in non-smoking homes (self-reported) were not significantly different (n = 10, R² = 0.937), while the difference between measurements for smoking homes was 44% (n = 31, R² = 0.773). Both OPC and DRX data had substantial and significant systematic and proportional biases compared with pDR-1500 readings. However, these methods were highly correlated: R² = 0.936 for OPC versus pDR-1500 reading and R² = 0.863 for DRX versus pDR-1500 reading. The data suggest that accuracy of aerosol mass concentrations from direct-reading instruments in indoor environments depends on the instrument, and that correction factors can be used to reduce biases of these real-time monitors in residential green buildings with similar aerosol properties.

Implications: This study used several real-time and filter-based aerosol instruments to measure PM_2.5 levels in a high-rise residential green building in the northeastern United States and compared performance of those instruments. The data show that while the use of real-time monitors is convenient for measurement of airborne PM at short time scales, the accuracy of those monitors depends on a particular instrument. Bias correction factors identified in this paper could provide guidance for other studies using direct-reading instruments to measure PM concentrations.     

Evaluation of Time-Resolved PM2.5 Data in Urban/Suburban Areas of New Jersey

ABSTRACT

Time-resolved data is needed for public notification of unhealthful air quality and to develop an understanding of atmospheric chemistry, including insights important to control strategies. In this research, continuous fine particulate matter (PM_2.5) mass concentrations were measured with tapered element oscillating microbalances (TEOMs) across New Jersey from July 1997 to June 1998. Data features indicating the influence of local sources and long-distance transport are examined, as well as differences between 1-hr maxima and 24-hr average concentrations that might be relevant to acute health effects. Continuous mass concentrations were not significantly different from filter-collected gravimetric mass concentrations with 95% confidence intervals during any season. Annual mean PM_2.5 concentrations from July 1997 to June 1998 were 17.3, 16.4, 14.1, and 15.3 μg/m³ at Newark, Elizabeth, New Brunswick, and Camden, NJ, respectively. Monthly averaged 24- and 1-hr daily maximum PM_2.5 concentrations suggest the existence of a high PM_2.5 (May-October) and a low PM_2.5 (November-April) season.

PM_2.5 magnitudes and temporal trends were very similar across the state during high PM_2.5 events. In fact, the between-site coefficients of determination (R²) for daily PM_2.5 measurements were 84-98% for June and July. Additionally, during the most pronounced PM_2.5 episode, PM_2.5 concentrations closely tracked the daily maximum 1-hr O₃ concentrations. These observations suggest the importance of transport and atmospheric chemistry (i.e., secondary formation) to PM_2.5 episodes in New Jersey. The influence of local sources was observed in diurnal concentration profiles and annual average between-site differences. Urban wintertime data illustrate that high 1-hr maximum PM_2.5 concentrations can occur on low 24-hr PM_2.5 days.     

Particulate matter source apportionment in a village situated in industrial region of Central Europe

The bilinear receptor model positive matrix factorization (PMF) was used to apportion particulate matter with an aerodynamic diameter of 1–10 μm (PM_1–10) sources in a village, B?ezno, situated in an industrial region of northern Bohemia in Central Europe. The receptor model analyzed the data sets of 90- and 60-min integrations of PM_1–10 mass concentrations and elemental composition for 27 elements. The 14-day sampling campaigns were conducted in the village in summer 2008 and winter 2010. Also, to ensure seasonal and regional representativeness of the data sets recorded in the village, the spatial-temporal variability of the 24-hr PM₁₀ and PM_1–10 within 2008–2010 in winter and summer across the multiple sites was evaluated. There were statistically significant interseasonal differences of the 24-hr PM data, but not intrasummer or intrawinter differences of the 24-hr PM_1–10 data across the multiple sites. PMF resolved seven sources of PM_1–10. They were high-temperature coal combustion; combustion in local heating boilers; marine aerosol; mineral dust; primary biological/wood burning; road dust, car brakes; and gypsum. The main summer factors were assigned to mineral dust (38.2%) and primary biological/wood burning (33.1%). In winter, combustion factors dominated (80%) contribution to PM_1–10. The conditional probability function (CPF) helped to identified local sources of PM_1–10. The source of marine aerosol from the North Sea and English Channel was indicated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT).

Implications: This is the first application of PMF to highly time/size resolved PM data in Czech Republic. The coarse aerosol fraction, PM_1–10, was chosen with regard to industrial character of the region, sampling site near the coal strip mine and coal power stations. Contrary to expectation, source apportionment did not show dominance of emissions from the coal strip mine. The results will enable local authorities and state bodies responsible for air quality assessment to focus on sources most responsible for air pollution in this industrial region.

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 for (1) details of measurement campaigns; (2) CPF for each of the sources contributing to PM_1–10; (3) factors contribution to PM_1–10 resolved by PMF; (4) diurnal pattern of road dust, car brake factor in summer and winter; (5) trajectories during the marine aerosol episode in winter 2010; and (6) temporal temperature, concentration, and wind speed relationships during the summer 2008 campaign and winter 2010 campaign.     

Source apportionment of emissions from light-duty gasoline vehicles and other sources in the United States for ozone and particulate matter

Federal Tier 3 motor vehicle emission and fuel sulfur standards have been promulgated in the United States to help attain air quality standards for ozone and PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm). The authors modeled a standard similar to Tier 3 (a hypothetical nationwide implementation of the California Low Emission Vehicle [LEV] III standards) and prior Tier 2 standards for on-road gasoline-fueled light-duty vehicles (gLDVs) to assess incremental air quality benefits in the United States (U.S.) and the relative contributions of gLDVs and other major source categories to ozone and PM_2.5 in 2030. Strengthening Tier 2 to a Tier 3-like (LEV III) standard reduces the summertime monthly mean of daily maximum 8-hr average (MDA8) ozone in the eastern U.S. by up to 1.5 ppb (or 2%) and the maximum MDA8 ozone by up to 3.4 ppb (or 3%). Reducing gasoline sulfur content from 30 to 10 ppm is responsible for up to 0.3 ppb of the improvement in the monthly mean ozone and up to 0.8 ppb of the improvement in maximum ozone. Across four major urban areas—Atlanta, Detroit, Philadelphia, and St. Louis—gLDV contributions range from 5% to 9% and 3% to 6% of the summertime mean MDA8 ozone under Tier 2 and Tier 3, respectively, and from 7% to 11% and 3% to 7% of the maximum MDA8 ozone under Tier 2 and Tier 3, respectively. Monthly mean 24-hr PM_2.5 decreases by up to 0.5 μg/m³ (or 3%) in the eastern U.S. from Tier 2 to Tier 3, with about 0.1 μg/m³ of the reduction due to the lower gasoline sulfur content. At the four urban areas under the Tier 3 program, gLDV emissions contribute 3.4–5.0% and 1.7–2.4% of the winter and summer mean 24-hr PM_2.5, respectively, and 3.8–4.6% and 1.5–2.0% of the mean 24-hr PM_2.5 on days with elevated PM_2.5 in winter and summer, respectively.

Implications: Following U.S. Tier 3 emissions and fuel sulfur standards for gasoline-fueled passenger cars and light trucks, these vehicles are expected to contribute less than 6% of the summertime mean daily maximum 8-hr ozone and less than 7% and 4% of the winter and summer mean 24-hr PM_2.5 in the eastern U.S. in 2030. On days with elevated ozone or PM_2.5 at four major urban areas, these vehicles contribute less than 7% of ozone and less than 5% of PM_2.5, with sources outside North America and U.S. area source emissions constituting some of the main contributors to ozone and PM_2.5, respectively.     

Modeling an air pollution episode in northwestern United States: Identifying the effect of nitrogen oxide and volatile organic compound emission changes on air pollutants formation using direct sensitivity analysis

Air quality impacts of volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from major sources over the northwestern United States are simulated. The comprehensive nested modeling system comprises three models: Community Multiscale Air Quality (CMAQ), Weather Research and Forecasting (WRF), and Sparse Matrix Operator Kernel Emissions (SMOKE). In addition, the decoupled direct method in three dimensions (DDM-3D) is used to determine the sensitivities of pollutant concentrations to changes in precursor emissions during a severe smog episode in July of 2006. The average simulated 8-hr daily maximum O₃ concentration is 48.9 ppb, with 1-hr O₃ maxima up to 106 ppb (40 km southeast of Seattle). The average simulated PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) concentration at the measurement sites is 9.06 μg m^?3, which is in good agreement with the observed concentration (8.06 μg m^?3). In urban areas (i.e., Seattle, Vancouver, etc.), the model predicts that, on average, a reduction of NO_x emissions is simulated to lead to an increase in average 8-hr daily maximum O₃ concentrations, and will be most prominent in Seattle (where the greatest sensitivity is??0.2 ppb per % change of mobile sources). On the other hand, decreasing NO_x emissions is simulated to decrease the 8-hr maximum O₃ concentrations in remote and forested areas. Decreased NO_x emissions are simulated to slightly increase PM_2.5 in major urban areas. In urban areas, a decrease in VOC emissions will result in a decrease of 8-hr maximum O₃ concentrations. The impact of decreased VOC emissions from biogenic, mobile, nonroad, and area sources on average 8-hr daily maximum O₃ concentrations is up to 0.05 ppb decrease per % of emission change, each. Decreased emissions of VOCs decrease average PM_2.5 concentrations in the entire modeling domain. In major cities, PM_2.5 concentrations are more sensitive to emissions of VOCs from biogenic sources than other sources of VOCs. These results can be used to interpret the effectiveness of VOC or NO_x controls over pollutant concentrations, especially for localities that may exceed National Ambient Air Quality Standards (NAAQS).

Implications: The effect of NO_x and VOC controls on ozone and PM_2.5 concentrations in the northwestern United States is examined using the decoupled direct method in three dimensions (DDM-3D) in a state-of-the-art three-dimensional chemical transport model (CMAQ). NO_x controls are predicted to increase PM_2.5 and ozone in major urban areas and decrease ozone in more remote and forested areas. VOC reductions are helpful in reducing ozone and PM_2.5 concentrations in urban areas. Biogenic VOC sources have the largest impact on O₃ and PM_2.5 concentrations.     

Particulate Air Pollution in Mexico City: A Collaborative Research Project

ABSTRACT

PM₁₀, PM₂₅, precursor gas, and upper-air meteorological measurements were taken in Mexico City, Mexico, from February 23 to March 22, 1997, to understand concentrations and chemical compositions of the city's particulate matter (PM). Average 24-hr PM₁₀ concentrations over the period of study at the core sites in the city were 75 H g/m³. The 24-hr standard of 150 μ g/m³ was exceeded for seven samples taken during the study period; the maximum 24-hr concentration measured was 542 μ g/m³. Nearly half of the PM₁₀ was composed of fugitive dust from roadways, construction, and bare land. About 50% of the PM₁₀ consisted of PM_2.5, with higher percentages during the morning hours. Organic and black carbon constituted up to half of the PM_2.5. PM concentrations were highest during the early morning and after sunset, when the mixed layers were shallow. Meteorological measurements taken during the field campaign show that on most days air was transported out of the Mexico City basin during the afternoon with little day-to-day carryover.     

Seasonal variations of particle-associated nitrosamines by gas chromatography–mass spectrometry in the atmospheric environment of Zonguldak, Turkey

A gas chromatography–mass spectrometry method has been proposed for the determination of low-level mutagenic and carcinogenic nitrosamines in particulate matter. The method includes the collection of particulate matters (PM_2.5 and PM₁₀) using a dichotomous Partisol 2025 sampler and extraction of the compounds from aqueous solution with dichloromethane/2-propanol after sonication with a slightly basic water solution prior to their GC-MS analysis in electron impact mode. The obtained recoveries of nitrosamines ranged from 92.4 to 99.2 %, and the precision of this method, as indicated by the relative standard deviations, was within the range of 0.95–2.46?%. The detection limits obtained from calculations using the GC-MS results based on S/N?=?3 were found within the range from 4 to 22 pg/m³. The predominant nitrosamines determined in particulate matter were N-nitrosodimethylamine, N-nitrosodiethylamine, N-nitrosodibutylamine and N-nitrosomorpholine. Furthermore, N-mono- and dinitrosopiperazine and N-nitrosoethylbutylamine were also determined. N-dinitrosopiperazine was detected in PM_2.5 samples at the highest concentrations of up to 22.85 ng/m³ and in PM_2.5–10 samples at concentrations up to 7.60 ng/m³ in winter, whereas it was found in PM_2.5 samples up to 5.15 ng/m³ and in PM_2.5–10 samples up to 3.12 ng/m³ in summer. The total concentrations of nitrosamines were up to 161.4 ng/m³ in fine and 53.90 ng/m³ in coarse fractions in winter, whereas in summer were up to 35.24 and 12.60 ng/m³, respectively. The concentration levels of nitrosamines fluctuated significantly within a year, with higher means and peak concentrations in the winter compared to that in the summertime. The seasonal variations of particle-associated nitrosamine concentrations were investigated together with their relationships with meteorological parameters using Pearson’s correlation analysis in the winter and summer periods. Analysis of variance was used to determine which concentrations of nitrosamines were statistically different from one another and, together with meteorological parameters and discriminant analysis, was used to classify the particle samples by particle size according to seasons. The classification results of the particle samples in different seasons were very satisfactory, allowing 99.5 % of cases to be correctly grouped.     

Assessing the relationship between personal particulate and gaseous exposures of senior citizens living in Baltimore, MD

We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (> 64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM2.5, PM10, SO4(2-), O3, NO2, SO2, and exhaust-related VOCs. Results of this study showed that longitudinal associations between ambient PM2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM2.5 exposures and resulting personal-ambient associations. Associations between personal PM2.5 exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM2.5 sources. Evidence for this was provided by SO4(2-) measurements, which can be thought of as a tracer for ambient PM2.5. For SO4(2-), personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM2.5 sources to personal PM2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments. Results also indicate that the potential for confounding by PM2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM2.5 exposures were not significantly correlated with personal exposures to PM2.5-10, PM2.5 of non-ambient origin, O3, NO2, and SO2. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM2.5 epidemiologic studies are unlikely to be due to confounding by the PM2.5 co-pollutants measured in this study.     

Spatial Factors Influencing Winter Primary Particle Sampling and Interpretation

ABSTRACT

Aerosol samplers collect material that is locally generated as well as that transported from upwind; knowing the extent of the area from which the sample is drawn is necessary for proper interpretation of sampler data. The U.S. Environmental Protection Agency (EPA) PM_2.5 monitoring guidelines recognize a conceptual hierarchy of sampler spatial representation, but provide no objective measures of a site’s spatial representativeness. A case study of a sampler tributary area in central California provides insights into the factors that determine a sampler’s spatial representation. Winter diurnal cycles of fine particle concentrations at places of habitation ranging from urban cores to small farm towns show a marked cycle that can be linked to local human activity. Assessment of the possible causes of the observed cycles leads to the hypothesis that local sources dominate primary particle mass in winter samples. The hypothesis was tested using a simple model to relate routine 24-hr PM₁₀ and PM_2.5 samples to a sampler’s surroundings. Model results indicate that even minor sources very close to a sampler will overwhelm any regional component in a sample. The results for the cases studied also demonstrate that, in winter, most coarse (PM_10-2.5) particles collected are less than 2 hr old, and most primary fine (PM_2.5) particles are less than 4 hr old. Even on days that are not truly “stagnant,” samplers are very strongly influenced by their immediate surroundings (distances less than 10 km), and only weakly influenced by regional emissions.

The implications for interpretation of sample analyses are as follows: 1. Typical PM sampling networks are unlikely to represent regional conditions;

2. Similarity of samples in time and space between widely separated samplers probably arises from sampling analogous local environments rather than a uniformly mixed regional air mass;

3. Even weak sources near a sampler will prevent regionally representative samples, so that “background” specification in models can be strongly skewed by misapplication of sampler data;

4. Source-receptor relationships within a single modeling grid cell can cause measured and modeled source impacts at a sampler to diverge by orders of magnitude, even for grid cells as small as 1 km; and

5. Differential deposition of coarse and fine particles will skew source apportionment by chemical tracers unless the tracers and the source emissions have the same size distribution.

     

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.     

Characterization and contribution to PM2.5 of semi-volatile aerosols in Paris (France)

Collocated PM_2.5 measurements using a conventional R&P TEOM (model 1400a) and a TEOM-FDMS were performed at a Paris urban background site during winter/summer field experiments. Results showed that conventional TEOM underestimates PM_2.5 mass concentrations by about 50% in winter and 35% in summer. They also confirmed that this negative sampling artifact, due to the volatilization of semi-volatile material (SVM) inside the instrument, cannot be accurately accommodated by a single correction factor because of SVM routine fluctuations. A basic filter-based investigation of the SVM chemical composition also indicated that SVM, measured by the TEOM–FDMS, is mainly formed by ammonium nitrate in winter while significant contributions of semi-volatile organic matter were observed in summer. The latter species was found to possibly account for more than 50% of secondary organic aerosol formed during summer afternoons. These findings call for more investigation of the SVM chemical composition, particularly during the summer season, in Paris and in Europe.     

Spatial and temporal variability of outdoor coarse particulate matter mass concentrations measured with a new coarse particle sampler during the Detroit Exposure and Aerosol Research Study

The Detroit Exposure and Aerosol Research Study (DEARS) provided data to compare outdoor residential coarse particulate matter (PM_10–2.5) concentrations in six different areas of Detroit with data from a central monitoring site. Daily and seasonal influences on the spatial distribution of PM_10–2.5 during Summer 2006 and Winter 2007 were investigated using data collected with the newly developed coarse particle exposure monitor (CPEM). These data allowed the representativeness of the community monitoring site to be assessed for the greater Detroit metro area. Multiple CPEMs collocated with a dichotomous sampler determined the precision and accuracy of the CPEM PM_10–2.5 and PM_2.5 data.CPEM PM_2.5 concentrations agreed well with the dichotomous sampler data. The slope was 0.97 and the R² was 0.91. CPEM concentrations had an average 23% negative bias and R² of 0.81. The directional nature of the CPEM sampling efficiency due to bluff body effects probably caused the negative CPEM concentration bias.PM_10–2.5 was observed to vary spatially and temporally across Detroit, reflecting the seasonal impact of local sources. Summer PM_10–2.5 was 5 μg m^?3 higher in the two industrial areas near downtown than the average concentrations in other areas of Detroit. An area impacted by vehicular traffic had concentrations 8 μg m^?3 higher than the average concentrations in other parts of Detroit in the winter due to the suspected suspension of road salt. PM_10–2.5 Pearson Correlation Coefficients between monitoring locations varied from 0.03 to 0.76. All summer PM_10–2.5 correlations were greater than 0.28 and statistically significant (p-value < 0.05). Winter PM_10–2.5 correlations greater than 0.33 were statistically significant (p-value < 0.05). The PM_10–2.5 correlations found to be insignificant were associated with the area impacted by mobile sources during the winter. The suspected suspension of road salt from the Southfield Freeway, combined with a very stable atmosphere, caused concentrations to be greater in this area compared to other areas of Detroit. These findings indicated that PM_10–2.5, although correlated in some instances, varies sufficiently across a complex urban airshed that that a central monitoring site may not adequately represent the population's exposure to PM_10–2.5.