Environmental exposure of road borders to zinc

Blok, J.

doi:10.1016/j.scitotenv.2004.12.073

Cited by 85 publications

(45 citation statements)

References 21 publications

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“…Leonzio and Pisani (1987) concluded that the distribution patterns of traffic-related metals followed a first-order kinetics equation and that the coefficient of decrease was − 0.034. Other workers have reported that the contents of all heavy metal contaminants in soils decreased exponentially with increasing distance from the roadside (Blok, 2005;Nabulo et al, 2006;Guo et al, 2007Guo et al, , 2008Yan et al, 2013). In our study, most of the distribution patterns (about 80.83%) showed similar characteristics and conformed to a first-order kinetics equation.…”

Section: Regression Models and Background Values Of Traffic-related Msupporting

confidence: 81%

“…The CFs of Cr, Cu, Zn, As and Cd and the PN values had their highest average values at site TTH, whereas the average CF of Pb at site DX was significantly higher than that at the other three sampling sites (Table 6). Previous studies have verified that increased contents of traffic-related metals are significantly related to the volume of traffic and the speed of the vehicles (Blok, 2005;Nabulo et al, 2006;Chen et al, 2010). In this study, the changes in PN value were not in step with the flow of vehicles, which was almost the same at the four sampling sites.…”

Section: Tablesupporting

confidence: 61%

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Identification of traffic-related metals and the effects of different environments on their enrichment in roadside soils along the Qinghai–Tibet highway

Zhang

Wang

Zhang

et al. 2015

Science of The Total Environment

147

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• Cr, Zn, Cu, As, Cd, and Pb in soils along the highway are related to the traffic.• There are three distribution patterns of the traffic-related metals in soils.• Regional differences had significant relationship with the enrichment levels.• Cd was the prior metal and the TTH was the key area for soil environment monitoring. The road transportation could affect roadside soils environment detrimentally, including heavy metal enrichment. In order to identify and evaluate the enrichment of heavy metals resulted from road transportation on the Tibetan Plateau, the 11 heavy metals (V, Cr, Co, Ni, Cu, Zn, As, Cd, Rb, Pb and Tl) in the topsoil (0-10 cm depth) from four sites along the Qinghai-Tibet highway were discussed in this study. Our results indicate that heavy metals such as Cr, Cu, Zn, As, Cd and Pb are related to road transportation. The content of most of these heavy metals in roadside soils decreased exponentially with the distance from the road, as did some of the Nemero Synthesis Indexes (PN values). The contamination factor for the traffic-related metals ranged from 0.56 (no pollution) to 5.67 (considerable pollution) and the Nemero Synthesis Indexes of these heavy metals ranged from 0.80 (no pollution) to 4.49 (severe pollution). Cd was of priority concern as it had the highest contamination factor. The highest PN value for these traffic-related heavy metals was found in soils at site TTH (alpine steppe). Although transportation contributed to the high contents of these traffic-related metals in roadside environments, regional differences such as wind and the terrain also had significant relationship with their enrichment in these roadside soils. The roadside distance at which there is a potential risk to livestock and wildlife from the contamination of soils by heavy metals should be determined scientifically along the Qinghai-Tibet highway, based on the different natural environments found in the region. a b s t r a c t a r t i c l e i n f o

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Section: Regression Models and Background Values Of Traffic-related Msupporting

confidence: 81%

Section: Tablesupporting

confidence: 61%

Identification of traffic-related metals and the effects of different environments on their enrichment in roadside soils along the Qinghai–Tibet highway

Zhang

Wang

Zhang

et al. 2015

Science of The Total Environment

147

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“…Al and Mg come from crustal source, which were the major contributors to the third component. The last component contained only Zn, which is identified as road dust released from tire wear and diesel fuels (Adachi and Tainosho, 2004;Blok, 2005;Longhin et al, 2016). The results in this study indicate that sources of PM 2.5 at CMU and DAK are primarily BB, road traffic, agricultural activities and re-suspension of soils.…”

Section: Principal Components Analysis (Pca)mentioning

confidence: 73%

Investigation of Biomass Burning Chemical Components over Northern Southeast Asia during 7-SEAS/BASELInE 2014 Campaign

Khamkaew

Chantara

Janta

et al. 2016

Aerosol Air Qual. Res.

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This study investigates the chemical components of biomass burning (BB) aerosols obtained from Doi Ang Khang (DAK; near BB source) and Chiang Mai University (CMU; an urban location) over northern Southeast Asia in dry season (March to mid-April) 2014. PM 2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 µm) samples were collected over a 24-h sampling period as a part of the Seven South East Asian Studies ) and CMU (90.7-93.1 µg m -3 ) were not significantly different (p > 0.05) and well correlated (r = 0.8), and likely originated from similar source origins. The number of fire hotspots was particularly high during 20-21 March (greater than 200) and, consequently, peaks of PM 2.5 were recorded at both sites. The most abundant elements at both sampling sites were K (49-50% of total elements), Al (26-31%), Mg (16%) and Zn (4-7%), whereas SO 4 2-(30-38% of total ions), NO 3 -(13-20%), Na + (16-20%) and NH 4 + (14-15%) were the most abundant ions. Concentrations of levoglucosan and K + (BB tracers) were well correlated (r = 0.5 for CMU and 0.7 for DAK) confirming that the PM 2.5 detected in these areas were mainly influenced by BB activity. Principal component analysis (PCA) revealed that BB, road traffic, agricultural activity and soil re-suspension were plausible sources of PM 2.5 over the study locations. Apart from local sources, the influence of long-range transport was also investigated by way of three-day backward trajectory analysis.

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“…For example, Pb and Zn originate mainly from anthropogenic activities (2,9,27). Major anthropogenic sources of ni are burning of coal and oil, production of cu, ni and Pb, mining operations, steel works and cement industry (25).…”

Section: Resultsmentioning

confidence: 99%