EPA Positive Matrix Factorization Research Articles

Determining spatial variability in PM2.5 source impacts across Detroit, MI

Abstract Intra-urban variability in air pollution source impacts was investigated using receptor modeling of daily speciated PM2.5 measurements collected at residential outdoor locations across Detroit, MI (Wayne County) as part of the Detroit Exposure and Aerosol Research Study (DEARS) during summer and winter from 2004 to 2006. Six areas were selected for the residential monitoring in the DEARS to capture impacts from different sources including local industry, motor vehicles, and upwind regional sources. PM2.5 measurements were also collected at the Allen Park, MI Chemical Speciation Network (CSN) site for comparison with the residential outdoor sites. Sources impacting PM2.5 were quantified using the EPA Chemical Mass Balance Model (CMB 8.2). Published source profiles were used as input to CMB along with a mixed industrial profile and a steel manufacturing profile obtained by applying the EPA Positive Matrix Factorization Model (PMF 4.0) to CSN data from a Midwestern U.S. site with industrial sources similar to Detroit. Major PM2.5 sources impacting the Allen Park and residential monitoring areas during DEARS included motor vehicles (24–36% by mass), secondary sulfate/coal combustion (17–35%), secondary nitrate (16–37%) and organic matter (17–21%). Road dust, steel manufacturing, and mixed industrial sources contributed less than 11% by mass. CMB source contribution estimates for Allen Park during the DEARS generally compared well to CMB estimates from the collocated year-long CSN measurements using the same source profiles. CMB source contributions during DEARS showed similar contributions across the residential monitoring areas for secondary sulfate/coal combustion and secondary nitrate consistent with regional impacts for these sources. Contributions from motor vehicles, steel manufacturing, and mixed industrial sources varied across the DEARS monitoring areas, indicating impacts from local sources within the Detroit airshed that may not be well characterized by the Allen Park monitoring location.

Characterization and source apportionment of particulate pollution in Colombo, Sri Lanka

Because of increasing use of vehicles and other human activities in metropolitan Colombo, Sri Lanka, a study of long– term airborne particulate monitoring at two fixed sites was initiated. The specific objectives were to measure the elemental composition of the coarse and fine air particles, to identify the trends in pollution, to identify the main pollutant sources, and to quantify the source contributions. Samples of airborne particulate matter (PM) in the < 2.5 and 2.5–10 µm size ranges (PM2.5 and PM10–2.5) were collected using “Gent” stacked filter samplers at two urban sites in Colombo. The Air Quality Monitoring Station (AQM) of the Central Environmental Authority (CEA) operated during the period of May 2000 to December 2005. The second site at Atomic Energy Authority (AEA) operated from May 2003 to December 2008. Twenty–four hour samples were collected on weekdays. The fine filter samples were analyzed for 18 elements by ED–XRF. The annual averages for PM10, PM2.5, and black carbon (BC) at the AQM station during 2000 – 2005 ranged from 50 to 100, 16 to 32, and 8 to 15 µg/m3, respectively. The fine fraction data set including BC and major elements (Na, Mg, Al, Si, Cl, Fe, Zn, Ni, Cu, V, S, Br, Pb, Cr, K, Ca and Ti) was analyzed using EPA–PMF (Positive Matrix Factorization) to explore the possible sources of the PM at the two study sites. Four factors were found at both sites. The common sources are motor vehicles, road dust, biomass and sea salt. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPILT) back–trajectory model was used to explore possible long range transport of pollution. Smoke and soil dust transboundary events were identified based on fine Si and K in the data base in 2003 and 2004.

Particulate Air Pollution and Acute Cardiorespiratory Hospital Admissions and Mortality Among the Elderly

It is known that particulate air pollution affects cardiorespiratory health; however, it is unclear which particle size fractions and sources of particles are responsible for the health effects. Daily levels of nucleation (<0.03 microm), Aitken (0.03-0.1 microm), accumulation (0.1-0.29 microm), and coarse mode (2.5-10 microm) particles, particles with diameter <2.5 microm (PM2.5), and gaseous pollutants were measured at central outdoor measurement sites in Helsinki, Finland between 1998 and 2004. We determined the associations of particles with daily cardiorespiratory mortality and acute hospital admissions among the elderly (>or=65 years). For the analyses we used Poisson generalized additive models and for the source apportionment of PM2.5 we used the EPA positive matrix factorization method. There was a suggestion of an association of hospital admissions for arrhythmia with Aitken mode particles and PM2.5 from traffic. Otherwise few associations were observed between various sizes and types of particles and either cardiovascular admissions or mortality. In contrast, most particle fractions had positive associations with admissions for pneumonia and asthma-chronic obstructive pulmonary disease (COPD). The strongest and most consistent associations were found for accumulation mode particles (3.1%; 95% confidence interval = 0.43-5.8 for pneumonia over the 5-day mean, and 3.8%; 1.3-6.3 for asthma-COPD at lag 0, for an interquartile increase in particles). We also found a positive association of respiratory mortality mainly with accumulation mode particles (5.1%; 1.2-9.0 at lag 0). All particle fractions including Aitken, accumulation, and coarse mode had especially adverse respiratory health effects among the elderly. Overall associations were stronger for respiratory than for cardiovascular outcomes.

Evaluation of the CMB and PMF models using organic molecular markers in fine particulate matter collected during the Pittsburgh Air Quality Study

This analysis investigated different possible strategies for source apportionment of airborne fine particulate matter (PM 2.5) using data collected as part of the Pittsburgh Air Quality Study (PAQS). More specifically, we apportioned the organic fraction of the winter and summer season PM 2.5 using two source–receptor models – the EPA Chemical Mass Balance 8.2 (CMB) and EPA Positive Matrix Factorization 1.1 (PMF) models – and tested several case scenarios with each model by varying either the chemical species or source profiles used as model input. Moreover, we added the constraint of selecting only individual molecular marker species with concentrations above their minimum quantitative limits. Model results suggest that the molecular marker and source profile selection can strongly affect the model, as reflected in the source contribution estimates determined by both CMB and PMF. Biomass burning and mobile emissions sources were identified by both models as being major source contributors in Pittsburgh. A third source was consistent with a meat cooking profile but was more likely a combination of cooking and secondary organic aerosol. As expected, the relative proportion of each source's contribution depended on both the season and on whether the CMB or PMF model was applied. Selecting fewer species in CMB resulted in less mass being apportioned, and an unrealistically large wood burning contribution estimate. Swapping a wildfire profile for one of the two wood burning profiles also resulted in less mass being apportioned in the winter. The results suggest that CMB can distinguish between fireplace burning and wildfire contributions when appropriate species are included. The gasoline/diesel split also varied by up to an order of magnitude, depending on which model was applied and which species were fit.

Source apportionment of PM10 and PM2.5 at Tocopilla, Chile (22°05’S, 70°12’W)

Tocopilla is located on the coast of Northern Chile, within an arid region that extends from 30 degrees S to the border with Perú. The major industrial activities are related to the copper mining industry. A measurement campaign was conducted during March and April 2006 to determine ambient PM10 and PM(2.5) concentrations in the city. The results showed significantly higher PM10 concentrations in the southern part of the city (117 microg/m3) compared with 79 and 80 (microg/m3) in the central and northern sites. By contrast, ambient PM2.5 concentrations had a more uniform spatial distribution across the city, around 20 (microg/m3). In order to conduct a source apportionment, daily PM10 and PM(2.5) samples were analyzed for elements by XRF. EPA's Positive Matrix Factorization software was used to interpret the results of the chemical compositions. The major source contributing to PM(2.5) at sites 1, 2 and 3, respectively are: (a) sulfates, with approximately 50% of PM2.5 concentrations at the three sites; (b) fugitive emissions from fertilizer storage and handling, with 16%, 21% and 10%; (c) Coal and residual oil combustion, with 15%, 15% and 4%; (d) Sea salt, 5%, 6% and 16%; (e) Copper ore processing, 4%, 5% and 15%; and (f) a mixed dust source with 11%, 7% and 4%. Results for PM10--at sites 1, 2 and 3, respectively--show that the major contributors are: (a) sea salt source with 36%, 32% and 36% of the PM10 concentration; (b) copper processing emissions mixed with airborne soil dust with 6.6%, 11.5% and 41%; (c) sulfates with 31%, 31% and 12%; (d) a mixed dust source with 16%, 12% and 10%, and (e) the fertilizer stockpile emissions, with 11%, 14% and 2% of the PM10 concentration. The high natural background of PM10 implies that major reductions in anthropogenic emissions of PM10 and SO2 would be required to attain ambient air quality standards for PM10; those reductions would curb down ambient PM(2.5) concentrations as well.

Effects of Air Pollution on Elderly All Respiratory, COPD, and Pneumonia Mortality and Hospital Admissions

ISEE-221 Objective: Respiratory mortality and hospital admissions have been associated with particulate and gaseous air pollutants in epidemiologic studies. We investigated for the first time the short-term effects of ambient ultrafine particles (<0.1 μm) and source-specific fine particles (PM2.5, <2.5μm) on cause-specific respiratory mortality and hospital admissions. Material and Methods: Daily levels of ultrafine particles, PM2.5, CO, NO2, and O3 were measured at central outdoor measurement sites during 1998 to 2004. The daily mortality and hospital admission counts of the elderly (≥65) for all-respiratory diseases (ICD 10: J00-J99), chronic obstructive pulmonary disease (COPD: J41, J44), and pneumonia (J12-J15, J16.8, J18) were obtained from national registers. For analyses we used Poisson regression and the generalized additive model in R. EPA-positive matrix factorization was used for the source apportionment of PM2.5. Four sources were identified: traffic, soil, coal combustion, and secondary particles. Results: There were a total of 26,095 all-respiratory, 6937 COPD, and 10,733 pneumonia hospital admissions, and 3701 all-respiratory, 1103 COPD, and 2169 pneumonia deaths. Mean ultrafine particle and PM2.5 levels were 9273 cm−3 and 9.5 μg/m3, respectively. Two-day mean of PM2.5 was associated with all-respiratory [1.9% (95% CI, 0.58–3.24)], COPD [2.7% (95% CI, 0.22–5.2)], and pneumonia [2.2% (95% CI, 0.22–4.2)] admissions. Carbon monoxide was associated with all-respiratory admissions over the 2-day mean [2.4% (95% CI, 0.8–4.0)]. Ultrafine particles were associated with all-respiratory and pneumonia admissions at 1-day lag, but associations were less consistent. All-respiratory and COPD mortality were positively associated with the same-day O3 levels. Of the PM2.5 sources, traffic was positively associated with all-respiratory and pneumonia admissions, and secondary particles with COPD mortality and admissions. Conclusions: Fine particles, at low levels, are associated with hospital admissions for respiratory diseases, COPD, and pneumonia among elderly persons.