Determination of PM2.5 sources using time-resolved integrated source and receptor models

Multivariate statistical techniques are applied to particulate matter (PM) and meteorological data to identify the sources responsible for evening PM spikes at Sunland Park, NM (USA). The statistical techniques applied are principal components analysis (PCA), redundancy analysis (RDA), and absolute principal components scores analysis (APCSA), and the data evaluated are 3-h average (6–9 p.m.) PM_2.5 mass and chemical composition and 1-h average PM_2.5 and PM₁₀ mass and environmental data collected in the winter of 2002. Although the interpretation of the data was complicated by the presence of sources which are likely changing in time (e.g. brick kilns), the multivariate analyses indicate that the evening high PM_2.5 is associated with burning-activities occurring to the south of Sunland Park, and these emissions are characterized by elevated Sb, Cl⁻, and elemental carbon; 68% of the PM_2.5 mass can be attributed to this source. The PM₁₀ evening peaks, on the other hand, are mainly caused by resuspended dust generated by vehicular movements south of the site and transported by the local terrain-induced drainage flow.     

PM source identification at Sunland Park, New Mexico, using a simple heuristic meteorological and chemical analysis

The causes for evening low-wind PM10 and PM2.5 peaks at Sunland Park, NM, were investigated by using wind sector analysis and by assessing relationships between PM loadings and meteorological parameters through canonical ordination analysis. Both PM10 and PM2.5 concentrations during the evening hours accounted for approximately 50% of their respective 24-hr averages, and the PM10 was mainly composed of coarse material (PM10-2.5 amounted to 77% of PM10). A wind sector analysis based on data from three surface meteorological monitoring stations in the region narrowed the potential source region for PM10 and PM2.5 to an area within a few kilometers south of Sunland Park. Canonical ordination analysis confirmed that the peak frequently occurred under stable conditions with weak southerly winds. Chemical analyses of PM showed that elemental and organic carbon (EC and OC, respectively) dominate PM2.5 and inorganic elements dominate PM10-2.5. The combined data for EC/OC, geologic elements, and various trace elements indicate that under low wind and stable conditions, traffic-related PM emissions (motor vehicle exhausts and re-suspended road dust) from the south of the site are the most likely sources for the evening PM10 and PM2.5 peaks.     

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.     

Effects of Wind Direction on Coarse and Fine Particulate Matter Concentrations in Southeast Kansas

Abstract

Field data for coarse particulate matter ([PM] PM₁₀) and fine particulate matter (PM_2.5) were collected at selected sites in Southeast Kansas from March 1999 to October 2000, using portable MiniVol particulate samplers. The purpose was to assess the influence on air quality of four industrial facilities that burn hazardous waste in the area located in the communities of Chanute, Independence, Fredonia, and Coffeyville. Both spatial and temporal variation were observed in the data. Variation because of sampling site was found to be statistically significant for PM₁₀ but not for PM_2.5. PM₁₀ concentrations were typically slightly higher at sites located within the four study communities than at background sites. Sampling sites were located north and south of the four targeted sources to provide upwind and downwind monitoring pairs. No statistically significant differences were found between upwind and downwind samples for either PM₁₀ or PM_2.5, indicating that the targeted sources did not contribute significantly to PM concentrations. Wind direction can frequently contribute to temporal variation in air pollutant concentrations and was investigated in this study. Sampling days were divided into four classifications: predominantly south winds, predominantly north winds, calm/variable winds, and winds from other directions. The effect of wind direction was found to be statistically significant for both PM₁₀ and PM_2.5. For both size ranges, PM concentrations were typically highest on days with predominantly south winds; days with calm/variable winds generally produced higher concentrations than did those with predominantly north winds or those with winds from “other” directions. The significant effect of wind direction suggests that regional sources may exert a large influence on PM concentrations in the area.     

Source apportionment of airborne particulate matter in Southeast Texas using a source-oriented 3D air quality model

A nested version of the source-oriented externally mixed UCD/CIT model was developed to study the source contributions to airborne particulate matter (PM) during a two-week long air quality episode during the Texas 2000 Air Quality Study (TexAQS 2000). Contributions to primary PM and secondary ammonium sulfate in the Houston–Galveston Bay (HGB) and Beaumont–Port Arthur (BPA) areas were determined.The predicted 24-h elemental carbon (EC), organic compounds (OC), sulfate, ammonium ion and primary PM_2.5 mass are in good agreement with filter-based observations. Predicted concentrations of hourly sulfate, ammonium ion, and primary OC from diesel and gasoline engines and biomass burning organic aerosol (BBOA) at La Porte, Texas agree well with measurements from an Aerodyne Aerosol Mass Spectrometer (AMS).The UCD/CIT model predicts that EC is mainly from diesel engines and majority of the primary OC is from internal combustion engines and industrial sources. Open burning contributes large fractions of EC, OC and primary PM_2.5 mass. Road dust, internal combustion engines and industries are the major sources of primary PM_2.5. Wildfire dominates the contributions to all primary PM components in areas near the fires. The predicted source contributions to primary PM are in general agreement with results from a chemical mass balance (CMB) model. Discrepancy between the two models suggests that further investigations on the industrial PM emissions are necessary.Secondary ammonium sulfate accounts for the majority of the secondary inorganic PM. Over 80% of the secondary sulfate in the 4 km domain is produced in upwind areas. Coal combustion is the largest source of sulfate. Ammonium ion is mainly from agriculture sources and contributions from gasoline vehicles are significant in urban areas.     

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.     

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).     

An integrated approach to identify the origin of PM10 exceedances

Purpose

This study was aimed to the development of an integrated approach for the characterization of particulate matter (PM) pollution events in the South of Italy.

Methods

PM₁₀ and PM_2.5 daily samples were collected from June to November 2008 at an urban background site located in Bari (Puglia Region, South of Italy). Meteorological data, particle size distributions and atmospheric dispersion conditions were also monitored in order to provide information concerning the different features of PM sources.

Results

The collected data allowed suggesting four indicators to characterize different PM₁₀ exceedances. PM_2.5/PM₁₀ ratio, natural radioactivity, aerosol maps and back-trajectory analysis and particle distributions were considered in order to evaluate the contribution of local anthropogenic sources and to determine the different origins of intrusive air mass coming from long-range transport, such as African dust outbreaks and aerosol particles from Central and Eastern Europe. The obtained results were confirmed by applying principal component analysis to the number particle concentration dataset and by the chemical characterization of the samples (PM₁₀ and PM_2.5).

Conclusions

The integrated approach for PM study suggested in this paper can be useful to support the air quality managers for the development of cost-effective control strategies and the application of more suitable risk management approaches.     

Temporal variations of fine and coarse particulate matter sources in Jeddah,Saudi Arabia

This study provides the first comprehensive analysis of the seasonal variations and weekday/weekend differences in fine (aerodynamic diameter <2.5 μm; PM_2.5) and coarse (aerodynamic diameter 2.5–10 μm; PM_2.5–10) particulate matter mass concentrations, elemental constituents, and potential source origins in Jeddah, Saudi Arabia. Air quality samples were collected over 1 yr, from June 2011 to May 2012 at a frequency of three times per week, and analyzed. The average mass concentrations of PM_2.5 (21.9 μg/m³) and PM₁₀ (107.8 μg/m³) during the sampling period exceeded the recommended annual average levels by the World Health Organization (WHO) for PM_2.5 (10 μg/m³) and PM₁₀ (20 μg/m³), respectively. Similar to other Middle Eastern locales, PM_2.5–10 is the prevailing mass component of atmospheric particulate matter at Jeddah, accounting for approximately 80% of the PM₁₀ mass. Considerations of enrichment factors, absolute principal component analysis (APCA), concentration roses, and backward trajectories identified the following source categories for both PM_2.5 and PM_2.5–10: (1) soil/road dust, (2) incineration, and (3) traffic; and for PM_2.5 only, (4) residual oil burning. Soil/road dust accounted for a major portion of both the PM_2.5 (27%) and PM_2.5–10 (77%) mass, and the largest source contributor for PM_2.5 was from residual oil burning (63%). Temporal variations of PM_2.5–10 and PM_2.5 were observed, with the elevated concentration levels observed for mass during the spring (due to increased dust storm frequency) and on weekdays (due to increased traffic). The predominant role of windblown soil and road dust in both the PM_2.5 and PM_2.5–10 masses in this city may have implications regarding the toxicity of these particles versus those in the Western world where most PM health assessments have been made in the past. These results support the need for region-specific epidemiological investigations to be conducted and considered in future PM standard setting.

Implications: Temporal variations of fine and coarse PM mass, elemental constituents, and sources were examined in Jeddah, Saudi Arabia, for the first time. The main source of PM_2.5–10 is natural windblown soil and road dust, whereas the predominant source of PM_2.5 is residual oil burning, generated from the port and oil refinery located west of the air sampler, suggesting that targeted emission controls could significantly improve the air quality in the city. The compositional differences point to a need for health effect studies to be conducted in this region, so as to directly assess the applicability of the existing guidelines to the Middle East air pollution.     

The Influence of Human Activity Patterns on Personal PM Exposure: A Comparative Analysis of Filter-Based and Continuous Particle Measurements

ABSTRACT

Particulate matter (PM) exposure data from the U.S. Environmental Protection Agency (EPA)-sponsored 1998 Baltimore and 1999 Fresno PM exposure studies were analyzed to identify important microenvironments and activities that may lead to increased particle exposure for select elderly (>65 years old) subjects. Integrated 24-hr filter-based PM_2.5 or PM₁₀ mass measurements [using Personal Environmental Monitors(PEMs)] included personal measurements, indoor and outdoor residential measurements, and measurements at a central indoor site and a community monitoring site. A subset of the participants in each study wore passive nephelometers that continuously measured (1-min averaging time) particles ranging in size from 0.1 to ~10 um. Significant activities and locations were identified by a statistical mixed model (p < 0.01) for each study population based on the measured PM_2.5 or PM₁₀ mass and time activity data. Elevated PM concentrations were associated with traveling (car or bus), commercial locations (store, office, mall, etc.), restaurants, and working.

The modeled results were compared to continuous PM concentrations determined by the nephelometers while participants were in these locations. Overall, the nephelometer data agreed within 6% of the modeled PM_2.5 results for the Baltimore participants and within ~20% for the Fresno participants (variability was due to zero drift associated with the nephelometer). The nephelom-eter did not agree as well with the PM₁₀ mass measurements, most likely because the nephelometer optimally responds to fine particles (0.3–2 um). Approximately one-half (54 ± 31%; mean ± standard deviation from both studies) of the average daily PM_2.5 exposure occurred inside residences, where the participants spent an average of 83 ± 10% of their time. These data also showed that a significant portion of PM_2.5 exposure occurred in locations where participants spent only 4–13% of their time.     

DEARS particulate matter relationships for personal,indoor, outdoor,and central site settings for a general population

This analysis provides the initial summary of PM_2.5 mass concentrations relationships for all seasons and participants for a general population in the Detroit Exposure and Aerosol Research Study (DEARS). The summary presented highlights the utility of the new methodologies applied, in addition to summarizing the particulate matter (PM) data.Results include the requirement to adjust the exposure data for monitor wearing compliance and measured environmental tobacco smoke (ETS) levels, even though the study design specified a non-smoking household. A 40% wearing compliance acceptance level was suggested as necessary to balance minimizing exposure misclassification (from poor compliance) and having sufficient data to conduct robust statistical analyses. An ETS threshold level equivalent to adding more than 1.5 μg m^?3 to the collected sample was found to be necessary to detect changes in the personal exposure factor (F_pex). It is not completely clear why such a large threshold level was necessary.Statistically significant spatial PM_2.5 gradients were identified in three of the six DEARS neighborhoods in Wayne County. These were expected, given the number of strong, localized PM sources in the Detroit (Michigan) metro area. Some residential outdoor bias levels compared with the central site at Allen Park exceeded 15%. After adjusting for ETS biases, the outdoor contributions to the personal exposure were typically larger by factors from 1.75 to 2.2 compared with those of the non-outdoor sources. The outdoor contribution was larger in the summer than in the winter, which is consistent with the fractions of time spent outdoors in the summer vs. the winter (6.7% vs. 1.1% of the time).Mean personal PM_2.5 cloud levels for the general population DEARS cohort ranged from 1.5 to 3.8 (after ETS adjustment) and were comparable to those reported previously. The personal exposure collections indoors were typically at least 13 times greater than those contributed outdoors.     

Chemical characteristics and source apportionment of PM<Subscript>2.5</Subscript> using PCA/APCS,UNMIX, and PMF at an urban site of Delhi,India

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM_2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM_2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM_2.5 was recorded as 121.9 ± 93.2 μg m^?3 (range 25.1–429.8 μg m^?3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ～17% of PM_2.5. Strong seasonal variation was observed in PM_2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM_2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM_2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM_2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM_2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM_2.5 from the north-west India and Pakistan were mostly pertinent.     

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%.     

An enhanced PM2.5 air quality forecast model based on nonlinear regression and back-trajectory concentrations

An enhanced PM_2.5 air quality forecast model based on nonlinear regression (NLR) and back-trajectory concentrations has been developed for use in the Louisville, Kentucky metropolitan area. The PM_2.5 air quality forecast model is designed for use in the warm season, from May through September, when PM_2.5 air quality is more likely to be critical for human health. The enhanced PM_2.5 model consists of a basic NLR model, developed for use with an automated air quality forecast system, and an additional parameter based on upwind PM_2.5 concentration, called PM24. The PM24 parameter is designed to be determined manually, by synthesizing backward air trajectory and regional air quality information to compute 24-h back-trajectory concentrations. The PM24 parameter may be used by air quality forecasters to adjust the forecast provided by the automated forecast system. In this study of the 2007 and 2008 forecast seasons, the enhanced model performed well using forecasted meteorological data and PM24 as input. The enhanced PM_2.5 model was compared with three alternative models, including the basic NLR model, the basic NLR model with a persistence parameter added, and the NLR model with persistence and PM24. The two models that included PM24 were of comparable accuracy. The two models incorporating back-trajectory concentrations had lower mean absolute errors and higher rates of detecting unhealthy PM2.5 concentrations compared to the other models.     

Source Profiles of Particulate Matter Emissions from a Pilot-Scale Boiler Burning North American Coal Blends

ABSTRACT

Recent awareness of suspected adverse health effects from ambient particulate matter (PM) emission has prompted publication of new standards for fine PM with aerodynamic diameter less than 2.5 μm (PM_2.5). However, scientific data on fine PM emissions from various point sources and their characteristics are very limited. Source apportionment methods are applied to identify contributions of individual regional sources to tropospheric particulate concentrations. The existing industrial database developed using traditional source measurement techniques provides total emission rates only, with no details on chemical nature or size characteristics of particulates. This database is inadequate, in current form, to address source-receptor relationships.

A source dilution system was developed for sampling and characterization of total PM, PM_2.5, and PM₁₀ (i.e., PM with aerodynamic diameter less than 10 μm) from residual oil and coal combustion. This new system has automatic control capabilities for key parameters, such as relative humidity (RH), temperature, and sample dilution. During optimization of the prototype equipment, three North American coal blends were burned using a 0.7-megawatt thermal (MW_t) pulverized coal-fired, pilot-scale boiler. Characteristic emission profiles, including PM_2.5 and total PM soluble acids, and elemental and carbon concentrations for three coal blends are presented.     

The Relationship between Cross-Sectional and Time Series Studies

Abstract

There is a dearth of information on dust emissions from sources that are unique to the U.S. Department of Defense testing and training activities. However, accurate emissions factors are needed for these sources so that military installations can prepare accurate particulate matter (PM) emission inventories. One such source, coarse and fine PM (PM₁₀ and PM_2.5) emissions from artillery backblast testing on improved gun positions, was characterized at the Yuma Proving Ground near Yuma, AZ, in October 2005. Fugitive emissions are created by the shockwave from artillery pieces, which ejects dust from the surface on which the artillery is resting. Other contributions of PM can be attributed to the combustion of the propellants. For a 155–mm howitzer firing a range of propellant charges or zones, amounts of emitted PM₁₀ ranged from ～19 g of PM₁₀ per firing event for a zone 1 charge to 92 g of PM₁₀ per firing event for a zone 5. The corresponding rates for PM_2.5 were ～9 g of PM_2.5 and 49 g of PM_2.5 per firing. The average measured emission rates for PM₁₀ and PM_2.5 appear to scale with the zone charge value. The measurements show that the estimated annual contributions of PM₁₀ (52.2 t) and PM_2.5 (28.5 t) from artillery backblast are insignificant in the context of the 2002 U.S. Environment Protection Agency (EPA) PM emission inventory. Using national–level activity data for artillery fire, the most conservative estimate is that backblast would contribute the equivalent of 5 x 10^–4% and 1.6 x 10^–3% of the annual total PM₁₀ and PM_2.5 fugitive dust contributions, respectively, based on 2002 EPA inventory data.     

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.     

PM composition and source reconciliation in Mexico City

PM_2.5 and PM₁₀ were collected during 24-h sampling intervals from March 1st to 31st, 2006 during the MILAGRO campaign carried out in Mexico City's northern region, in order to determine their chemical composition, oxidative activity and the estimation of the source contributions during the sampling period by means of the chemical mass balance (CMB) receptor model. PM_2.5 concentrations ranged from 32 to 70 μg m⁻³ while that of PM10 did so from 51 to 132 μg m⁻³. The most abundant chemical species for both PM fractions were: OC, EC, SO₄²⁻, NO₃⁻, NH₄⁺, Si, Fe and Ca. The majority of the PM mass was comprised of carbon, up to about 52% and 30% of the PM2.5 and PM10, respectively. PM2.5 constituted more than 50% of PM10. The redox activity, assessed by the dithiothreitol (DTT) assay, was greater for PM_2.5 than for PM₁₀, and did not display significant differences during the sampling period. The PM_2.5 source reconciliation showed that in average, vehicle exhaust emissions were its most important source in an urban site with a 42% contribution, followed by re-suspended dust with 26%, secondary inorganic aerosols with 11%, and industrial emissions and food cooking with 10% each. These results had a good agreement with the Emission Inventory. In average, the greater mass concentration occurred during O₃S that corresponds to a wind shift initially with transport to the South but moving back to the North. Taken together these results show that PM chemical composition, oxidative potential, and source contribution is influenced by the meteorological conditions.     

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.     

Seasonal and spatial trends in the sources of fine particle organic carbon in Israel,Jordan, and Palestine

A study of carbonaceous particulate matter (PM) was conducted in the Middle East at sites in Israel, Jordan, and Palestine. The sources and seasonal variation of organic carbon, as well as the contribution to fine aerosol (PM_2.5) mass, were determined. Of the 11 sites studied, Nablus had the highest contribution of organic carbon (OC), 29%, and elemental carbon (EC), 19%, to total PM_2.5 mass. The lowest concentrations of PM_2.5 mass, OC, and EC were measured at southern desert sites, located in Aqaba, Eilat, and Rachma. The OC contribution to PM_2.5 mass at these sites ranged between 9.4% and 16%, with mean annual PM_2.5 mass concentrations ranging from 21 to 25 ug m^?3. These sites were also observed to have the highest OC to EC ratios (4.1–5.0), indicative of smaller contributions from primary combustion sources and/or a higher contribution of secondary organic aerosol. Biomass burning and vehicular emissions were found to be important sources of carbonaceous PM in this region at the non-southern desert sites, which together accounted for 30%–55% of the fine particle organic carbon at these sites. The fraction of measured OC unapportioned to primary sources (1.4 μgC m^?3 to 4.9 μgC m^?3; 30%–74%), which has been shown to be largely from secondary organic aerosol, is relatively constant at the sites examined in this study. This suggests that secondary organic aerosol is important in the Middle East during all seasons of the year.