Source Apportionment of Indoor, Outdoor, and Personal PM<sub>2.5</sub>in Seattle, Washington, Using Positive Matrix Factorization

Larson, Timothy V.; Gould, Timothy; Simpson, Christopher D.; Liu, L.-J. Sally; Claiborn, Candis; Lewtas, Joellen

doi:10.1080/10473289.2004.10470976

Cited by 102 publications

(68 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…S, V and Pb) was in line with results reported by others (Janssen et al, 2005;Larson et al, 2004;Oglesby et al, 2000). With regard to personal exposure v. indoor levels, the highest and most persistent correlations between personal exposure and outdoor levels (residential or urban background) were found for S and Pb, which are mostly of LRT origin with no indoor sources (Janssen et al, 2005).…”

Section: Personal Exposure V Indoor and Outdoor Levelssupporting

confidence: 90%

“…The elements that were significantly higher in the personal exposure in Papers II and/or Paper III were mostly of crustal nature and could be attributed to transport of soil from outdoors. Similar results, with higher estimates for personal exposure of this group of elements compared with indoor and outdoor levels, have been found by others (Kinney et al, 2000;Lai et al, 2004;Larson et al, 2004). The reason for the higher personal exposure is most likely indoor activities, both movement and other activities such as cooking.…”

Section: Personal Exposure V Indoor and Outdoor Levelssupporting

confidence: 89%

“…These were performed in Amsterdam and Helsinki (Janssen et al, 2005), New York (Kinney et al, 2002), Oxford (Lai et al, 2004) and Seattle (Larson et al, 2004), while in a study performed in Basel (Oglesby et al, 2000) only personal exposure and outdoor levels were sampled. The mean personal exposure and indoor and outdoor levels in these studies together with the levels in Papers II-IV are presented in Tables 5.1-5.3.…”

Section: Personal Exposure and Indoor And Outdoor Levels Of Trace Elementioning

confidence: 99%

See 2 more Smart Citations

Personal exposures and indoor, residential outdoor, and urban background levels of fine particle trace elements in the general population

et al. 2006

View full text Add to dashboard Cite

The general population is exposed to particulate air pollution from many different local and regional sources. Examples of local sources are traffic, biomass burning and resuspended dust, while regional sources are dominated by combustion processes from heating, traffic and industries. The overall aim of this thesis was to characterise the personal exposure to trace elements in fine particles, mainly PM 2.5 and investigate how the exposure is related to indoor and outdoor levels. Particulate matter was collected on filters and analysed for elemental content by X-ray fluorescence (XRF) spectroscopy.In the general population in Göteborg, personal exposures to Cl, Ca, Ti and Fe were significantly higher compared with indoor, residential outdoor and urban background levels. Significant correlations were also found between urban background PM mass and personal exposure to elements related to both combustion (S, V and Pb) and resuspended dust (Ti, Fe and Zn), indicating that both sources could be relevant for health effects from urban background PM. In a community where wood burning for domestic heating is common, significantly (66-80%) higher personal exposures and indoor levels were found for K, Ca and Zn compared with a reference group living in the same area, indicating that these elements could be good markers for wood smoke. In a study in Stockholm concerning children's environments (home, school and preschool), higher indoor than outdoor levels of Ti were found, while long-range-transported (LRT) elements (S, Ni, Br and Pb) were higher outdoors. A community located 25 km from the city centre had significantly lower outdoor levels of crustal and traffic-related elements compared with both the city centre and a suburban area. The levels of Fe and Cu were four times higher in the central communities. Outdoors, Cu levels were found to correlate well with the traffic marker NO 2 , making it a possible elemental marker for traffic-related aerosols in health studies. Roadside measurements of fine and ultrafine (<100 nm) particles were performed along a major approach road to Göteborg and the levels of ultrafine particles were influenced not only by traffic intensity, but also, by wind speed and direction, as well as boundary layer height. No correlation was found between PM 2.5 and ultrafine particles or traffic, but there was a correlation between PM 2.5 and particles sized 100-368 nm. In all environments studied, the origin of LRT air masses had a strong effect on exposure and levels of PM elements.In conclusion, this thesis demonstrates that elemental analysis is a useful method for better characterising human exposure to fine particles. For several elements, the personal exposure is often higher than corresponding indoor levels. The origin of LRT elements affected not only outdoor levels, but also, the personal exposure and indoor levels, and should be taken into account in time series studies of air pollution and health.

show abstract

Section: Personal Exposure V Indoor and Outdoor Levelssupporting

confidence: 90%

Section: Personal Exposure V Indoor and Outdoor Levelssupporting

confidence: 89%

Section: Personal Exposure and Indoor And Outdoor Levels Of Trace Elementioning

confidence: 99%

See 1 more Smart Citation

Personal exposures and indoor, residential outdoor, and urban background levels of fine particle trace elements in the general population

et al. 2006

View full text Add to dashboard Cite

show abstract

“…: +46-31-786 2857; Fax: +46-31-82 50 04 E-mail address: peter.molnar@amm.gu.se exposure (Oglesby et al, 2000;Sarnat et al, 2005;Sorensen et al, 2005;Johannesson et al, 2007). Some studies have also characterized the chemical composition of the PM 2.5 in personal exposures (Yakovleva et al, 1999;Oglesby et al, 2000;Kinney et al, 2002;Lai et al, 2004;Larson et al, 2004;Janssen et al, 2005;Molnár et al, 2005;Molnár et al, 2006;Zhao et al, 2006;Johannesson et al, 2011). The infiltration of ambient air indoors can be calculated using elements with no indoor sources (e.g., S or Pb), and thus, the influence of ambient air on indoor air can be assessed (Hänninen et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Source Apportionment of PM2.5 Using Positive Matrix Factorization (PMF) and PMF with Factor Selection

Molnár

Johannesson

Quaß

2014

Aerosol Air Qual. Res.

View full text Add to dashboard Cite

Personal exposure, indoor, residential outdoor and urban background particulate matter (PM 2.5 ) samples were collected in parallel, for 30 participants and analyzed for their chemical content. Source apportionments for the separate microenvironments were performed using conventional positive matrix factorization (PMF), and for the combined dataset, applying a new PMF method with factor selection.Regional sources were the largest contributor to the sampled PM 2.5 in all microenvironments and accounted for 69% in urban background; 55% and 54% in residential outdoor and indoor environment, respectively; and 40% of personal exposure. For personal exposure, personal activities accounted for 21% (2.2 µg/m 3 ), and constituted the main difference in total mass concentration between personal exposure and the other microenvironments.The PMF method with factor selection was found to be a useful tool in the PMF analysis of multiple microenvironments, since ambient contributions to indoor and personal exposure are less likely to be distorted or misinterpreted. The possibility to more correctly estimate the source contributions will increase by combining the datasets for the different microenvironments into a larger dataset and using the PMF with factor selection method.

show abstract

“…In Accra, traffic-related emissions accounted for 12−33% (7−12 μg/m 3 ) of household PM 2.5 mass concentration, compared with only 3−8% (0.3−1.3 μg/m 3 ) in some studies in high-income countries. 28,29 The higher contribution of traffic-related emissions in Accra may be due to poor road and car conditions (mostly unpaved roads and a large number of imported used high-emission cars). If African cities follow the motorization trend of Asian and Middle Eastern megacities, then there will be even more traffic-related pollution.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

Chemical Characterization and Source Apportionment of Household Fine Particulate Matter in Rural, Peri-urban, and Urban West Africa

Zhou

Dionisio

Veríssimo

et al. 2014

Environ. Sci. Technol.

View full text Add to dashboard Cite

Household air pollution in sub-Saharan Africa and other developing regions is an important cause of disease burden. Little is known about the chemical composition and sources of household air pollution in subSaharan Africa, and how they differ between rural and urban homes. We analyzed the chemical composition and sources of fine particles (PM 2.5 ) in household cooking areas of multiple neighborhoods in Accra, Ghana, and in peri-urban (Banjul) and rural (Basse) areas in The Gambia. In Accra, biomass burning accounted for 39−62% of total PM 2.5 mass in the cooking area in different neighborhoods; the absolute contributions were 10−45 μg/m 3 . Road dust and vehicle emissions comprised 12−33% of PM 2.5 mass. Solid waste burning was also a significant contributor to household PM 2.5 in a low-income neighborhood but not for those living in better-off areas. In Banjul and Basse, biomass burning was the single dominant source of cooking-area PM 2.5 , accounting for 74−87% of its total mass; the relative and absolute contributions of biomass smoke to PM 2.5 mass were larger in households that used firewood than in those using charcoal, reaching as high as 463 μg/m 3 in Basse homes that used firewood for cooking. Our findings demonstrate the need for policies that enhance access to cleaner fuels in both rural and urban areas, and for controlling traffic emissions in cities in sub-Saharan Africa.

show abstract

Source Apportionment of Indoor, Outdoor, and Personal PM_2.5in Seattle, Washington, Using Positive Matrix Factorization

Cited by 102 publications

References 32 publications

Personal exposures and indoor, residential outdoor, and urban background levels of fine particle trace elements in the general population

Personal exposures and indoor, residential outdoor, and urban background levels of fine particle trace elements in the general population

Source Apportionment of PM2.5 Using Positive Matrix Factorization (PMF) and PMF with Factor Selection

Chemical Characterization and Source Apportionment of Household Fine Particulate Matter in Rural, Peri-urban, and Urban West Africa

Contact Info

Product

Resources

About

Source Apportionment of Indoor, Outdoor, and Personal PM2.5in Seattle, Washington, Using Positive Matrix Factorization

Cited by 102 publications

References 32 publications

Personal exposures and indoor, residential outdoor, and urban background levels of fine particle trace elements in the general population

Personal exposures and indoor, residential outdoor, and urban background levels of fine particle trace elements in the general population

Source Apportionment of PM2.5 Using Positive Matrix Factorization (PMF) and PMF with Factor Selection

Chemical Characterization and Source Apportionment of Household Fine Particulate Matter in Rural, Peri-urban, and Urban West Africa

Contact Info

Product

Resources

About

Source Apportionment of Indoor, Outdoor, and Personal PM_2.5in Seattle, Washington, Using Positive Matrix Factorization