Small-scale spatial variability of particulate matter &lt; 10 μm (PM10) and nitrogen dioxide

Monn, Christian; Carabias-Hütter, Vicente; Junker, Martin H.; Waeber, Roger; Karrer, Markus; Wanner, H. U.

doi:10.1016/s1352-2310(97)00030-7

Cited by 77 publications

(26 citation statements)

References 9 publications

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“…The smallest ranges were observed for PM 2.5 mass concentrations in all three centers. A small spatial variability in PM 10 concentrations within an urban and between urban and non-urban areas was observed also in other studies (Hoek et al, 1997a;Monn et al, 1997;Cyrys et al, 1998). A major fraction of PM 2.5 consists of secondary pollutants (sulfates, nitrates), which are formed within the atmosphere from gas-to-particle conversion processes.…”

Section: Discussionsupporting

confidence: 82%

Comparison between different traffic-related particle indicators: Elemental carbon (EC), PM2.5 mass, and absorbance

Cyrys

Heinrich

Hoek

et al. 2003

J Expo Sci Environ Epidemiol

209

138

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Here we compare PM 2.5 (particles with aerodynamic diameter less than 2.5 mm) mass and filter absorbance measurements with elemental carbon (EC) concentrations measured in parallel at the same site as well as collocated PM 2.5 and PM 10 (particles with aerodynamic diameter less than 10 mm) mass and absorbance measurements. The data were collected within the Traffic-Related Air Pollution on Childhood Asthma (TRAPCA) study in Germany, The Netherlands and Sweden. The study was designed to assess the health impact of spatial contrasts in long-term average concentrations. The measurement sites were distributed between background and traffic locations. Annual EC and PM 2.5 absorbance measurements were at traffic sites on average 43-84% and 26-76% higher, respectively, compared to urban background sites. The contrast for PM 2.5 mass measurements was lower (8-35%). The smaller contrast observed for PM 2.5 mass in comparison with PM 2.5 absorbance and EC documents that PM 2.5 mass underestimates exposure contrasts related to motorized traffic emissions. The correlation between PM 10 and PM 2.5 was high, documenting that most of the spatial variation of PM 10 was because of PM 2.5 . The measurement of PM 2.5 absorbance was highly correlated with EC measurements and suggests that absorbance can be used as a simple, inexpensive and non-destructive method to estimate motorized traffic-related particulate air pollution. The EC/absorbance relation differed between countries and site type (background/traffic), supporting the need for site-specific calibrations of the simple absorbance method. While the ratio between PM 2.5 and PM 10 mass ranged from 0.54 to 0.68, the ratio of PM 2.5 absorbance and PM 10 absorbance was 0.96-0.97, indicating that PM 2.5 absorbance captures nearly all of the particle absorbance.

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Section: Discussionsupporting

confidence: 82%

Comparison between different traffic-related particle indicators: Elemental carbon (EC), PM2.5 mass, and absorbance

Cyrys

Heinrich

Hoek

et al. 2003

J Expo Sci Environ Epidemiol

209

138

View full text Add to dashboard Cite

show abstract

“…1). We used a 500-foot radius because this approximates the distance from a road at which pollutant concentrations are the highest based on available monitoring data (36)(37)(38). We calculated traffic density by summing the VMT for all road segments and dividing by the buffered area (0.028 mi where TD is traffic density (vehicles Â miles/d/mi 2 ), AADT is annual average daily traffic (vehicles/d), L is length of road segment (miles), and A B is buffered area (mi 2 ).…”

Section: Methodsmentioning

confidence: 99%

Estimating Exposure to Polycyclic Aromatic Hydrocarbons: A Comparison of Survey, Biological Monitoring, and Geographic Information System–Based Methods

Gunier

Reynolds

Hurley

et al. 2006

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Our objective was to compare polycyclic aromatic hydrocarbon (PAH) exposure estimates based on survey, biological monitoring, and geographic information system (GIS) methods. The 304 participants in this study supplied a urine sample and completed questionnaires about exposure to potential PAH sources. We assayed urine samples for 1-hydroxypyrene-O -glucuronide (1-OHPG), the major metabolite of pyrene, a common PAH. We used a GIS to estimate traffic exhaust exposure using vehicle count data at the residence and workplace. The five subjects who reported smoking during the 48-hour period had median 1-OHPG concentrations 10-fold that of nonsmokers (1.6 versus 0.16 pmol/mL; P = 0.01). Among nonsmokers, those who reported eating grilled, roasted, or broiled meat had significantly higher 1-OHPG concentrations than those who did not reported eating meat prepared by these methods (0.25 versus 0.06 pmol/mL; P = 0.02). Nonsmokers who reported traveling on roads for z3 hours during the 48-hour period also had significantly higher 1-OHPG levels than those who traveled <3 hours (0.23 versus 0.11 pmol/ mL; P = 0.03). 1-OHPG levels were also correlated with hours of secondhand smoke exposure among nonsmokers (P = 0.04). In this study, 1-OHPG urine concentrations were not associated with self-reported exposures to cooking smoke, wood burning, or traffic levels near the home or to traffic density or urban/rural status determined using a GIS. Self-reported indicators of residential proximity to high traffic volume were, however, associated with GIS traffic density measures. (Cancer Epidemiol Biomarkers Prev 2006;15(7):1376 -81)

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“…[5][6][7]11,12 Several studies have used Pearson correlation coefficients to characterize spatial variability in ambient air pollutant concentrations. [13][14][15][16][17] Other studies have used analysis of variance to characterize variability in air pollutant concentrations between specific monitoring sites. 18 -20 Analysis of variance provides a measure of variation between monitoring sites relative to variation over time at one monitoring site and is particularly useful when several sites with different average concentrations are considered.…”

Section: Introductionmentioning

confidence: 99%

Effects of Instrument Precision and Spatial Variability on the Assessment of the Temporal Variation of Ambient Air Pollution in Atlanta, Georgia

Wade

Mulholland

Marmur

et al. 2006

Journal of the Air & Waste Management Association

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Small-scale spatial variability of particulate matter < 10 μm (PM10) and nitrogen dioxide

Cited by 77 publications

References 9 publications

Comparison between different traffic-related particle indicators: Elemental carbon (EC), PM2.5 mass, and absorbance

Comparison between different traffic-related particle indicators: Elemental carbon (EC), PM2.5 mass, and absorbance

Estimating Exposure to Polycyclic Aromatic Hydrocarbons: A Comparison of Survey, Biological Monitoring, and Geographic Information System–Based Methods

Effects of Instrument Precision and Spatial Variability on the Assessment of the Temporal Variation of Ambient Air Pollution in Atlanta, Georgia

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