Multielemental characterization of urban roadway dust

Hopke, Philip K.; Lamb, Robert E.; Natusch, D. F. S.

doi:10.1021/es60162a006

Cited by 291 publications

(104 citation statements)

References 11 publications

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“…Multiple linear regression was applied to regress the total PM 10 mass against the estimated source contributions (Hopke et al 1980). The regression coefficients should all be positive if the resolved sources are reasonable.…”

Section: Positive Matrix Factorization and Conditional Probability Fumentioning

confidence: 99%

PM10 source apportionment in the surroundings of the San Vicente del Raspeig cement plant complex in southeastern Spain

Yubero

Carratalá

Crespo

et al. 2010

Environ Sci Pollut Res

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Introduction The concentrations of trace metals, ionic species, and carbonaceous components in PM 10 (particulate matter with aerodynamic diameters smaller than 10 µm) were measured from samples collected near an industrial complex, primarily composed of cement plants, in southeastern Spain, from September 2005 to August 2006. Materials and methods Positive matrix factorization and conditional probability function were applied to this data set to identify different types of sources. Results Six significant sources were identified: crustal matter, traffic, aged sea salt, industrial emissions, secondary aerosol, and sea salt. The difficulty of separating anthropogenic sources from those of natural origin is highlighted in this study; in particular, the crustal source can be connected with both natural (African outbreaks, wind resuspension) and man-made emissions, like fugitive emissions in an industrial environment.

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Section: Positive Matrix Factorization and Conditional Probability Fumentioning

confidence: 99%

PM10 source apportionment in the surroundings of the San Vicente del Raspeig cement plant complex in southeastern Spain

Yubero

Carratalá

Crespo

et al. 2010

Environ Sci Pollut Res

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“…To estimate source contributions and source profiles in actual units for these matrices, scaling coefficients were obtained using a multiple linear regression against the measured PM 2.5 mass. 34 Figure 2 shows the source profiles obtained for the nine-factor PMF solution at 4th Street, San Jose. Figure 3 presents the time series of contributions from each source.…”

Section: Source Contributions At 4th Streetmentioning

confidence: 99%

Comparison of Source Apportionments of Fine Particulate Matter at Two San Jose Speciation Trends Network Sites

Hwang

Hopke

2006

Journal of the Air & Waste Management Association

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In this study, the chemical composition of fine particulate matter samples collected at U.S. Environmental Protection Agency Speciation Trends Network sites in San Jose, CA, from February 2000 to February 2005 were analyzed. A San Jose site was initially established at 4th Street and then subsequently moved to Jackson Street in mid-2002. These sites are ϳ1 km apart. There were no known major changes in the nature of the sources in the area over this period. The study used positive matrix factorization model to extract the source profiles and their mass contributions and to compare the results for the congruence of the source apportionments between these two nearby sites. In the case of the 4th Street site, the average mass was apportioned to wood combustion (32.1 Ϯ 2.5%), secondary nitrate (22.3 Ϯ 2%), secondary sulfate (10.7 Ϯ 0.6%), fresh sea salt (7.7 Ϯ 0.9%), gasoline vehicles (7.3 Ϯ 0.5%), aged sea salt (6.8 Ϯ 0.4%), road dust (6.7 Ϯ 0.7%), diesel emissions (3.9 Ϯ 0.3%), and a Ni-related industrial source (2.5 Ϯ 0.4%). At the Jackson Street site, the average mass was apportioned to wood combustion (33.6 Ϯ 2.6%), secondary nitrate (20.3 Ϯ 1.9%), secondary sulfate (13.9 Ϯ 0.9%), aged sea salt (12.4 Ϯ 0.7%), gasoline vehicle (8.3 Ϯ 0.6%), fresh sea salt (5.3 Ϯ 0.5%), diesel emission (3.2 Ϯ 0.3%), road dust (1.9 Ϯ 0.1%), and Ni-related industrial source (1.3 Ϯ 0.1%). Conditional probability function analysis was used to help identify local sources. These results suggested that moving the sampling site a short distance had little effect on the nature of the resolved source types although some differences in their quantitative impacts were obtained in the positive matrix factorization analyses.

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“…1). The major urban sources of zinc have been suggested as tyres (Christensen & Guinn 1979;Hopke et al 1980) and galvanised iron roofing (Harremoes 1982). The higher proportion of roofs connected to the stormwater system in the Wairau catchment may be a factor in the concentrations found there.…”

Section: Discussionmentioning

confidence: 99%

“…The higher proportion of roofs connected to the stormwater system in the Wairau catchment may be a factor in the concentrations found there. Cd is considered to arise from contamination of zinc or from vehicle exhaust (Hopke et al 1980). Soil must supply a significant proportion of the Cu found, but these levels are enriched, possibly by vehicle emissions such as brake-lining wear (Shaheen 1975).…”

Section: Discussionmentioning

confidence: 99%

Urban stormwater quality II. Comparision of three New Zealand catchments

Williamson

1986

New Zealand Journal of Marine and Freshwater Research

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The variability in water quality of urban runoff was assessed by comparing the concentration distributions and variations of various parameters over storm events in three catchments. The parameters chosen assessed nutrient, total oxygen demand, sediment, and toxic metal levels. Two catchments were located in Wairau Valley, Takapuna, Auckland. The smaller (1.49 km 2 ), with residential/commercial landuse, formed part of the larger (11 km 2 ) with predominantly residential/industrial/developing land. The third was a 1.14 km 2 residential catchment in Hillcrest, Hamilton. The greatest dissimilarity occurred between the Hillcrest and the two Auckland catchments. Concentrations of suspended solids, total phosphorus, dissolved reactive phosphorus, Cr, Ni, and Zn were significantly higher in the Auckland catchments, whereas chemical oxygen demand, organic nitrogen, Pb, and volatile suspended solids were not significantly different from Hillcrest. NH 4 + levels were higher in Hillcrest. Storm flows diluted NO 3 -concentrations in Hillcrest but increased NO 3 -concentrations in the Auckland catchments, resulting in comparable levels in all three catchments. It is proposed that most of the differences are attributable to higher specific flows and subsoil erosion in the Auckland catchments coupled with dissimilarities in soil concentrations and characteristics. The differences in the variation of NO 3 -concentrations were probably because of septic tank seepage in the Hillcrest catchment. The largest catchment differed from the two smaller catchments in having higher Cu and slightly lower TN and NO 3 -levels. All three catchments showed some similarities: Pb, Zn, and probably Cu and Cd were clearly enriched in the suspended sediment over Received 7 June 1985; accepted 19 August 1985 background soil levels, and P, organic matter (COD, ON, VSS), Cr, and Ni were not enriched. It was concluded that geographical differences were more important in determining stormwater quality than urban infrastructure.

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Multielemental characterization of urban roadway dust

Cited by 291 publications

References 11 publications

PM10 source apportionment in the surroundings of the San Vicente del Raspeig cement plant complex in southeastern Spain

PM10 source apportionment in the surroundings of the San Vicente del Raspeig cement plant complex in southeastern Spain

Comparison of Source Apportionments of Fine Particulate Matter at Two San Jose Speciation Trends Network Sites

Urban stormwater quality II. Comparision of three New Zealand catchments

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