Quantitative source tracking of heavy metals contained in urban road deposited sediments

Hong, Nian; Guan, Yingjie; Yang, Bo; Zhong, Jie; Zhu, Panfeng; Ok, Yong Sik; Hou, Deyi; Tsang, Daniel C.W.; Guan, Yuntao; Liu, An

doi:10.1016/j.jhazmat.2020.122362

Cited by 72 publications

(35 citation statements)

References 52 publications

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“…Of all the target elements, the bioaccessibility was the highest for Zn (Figure 3b) in both size fractions extracted with AC (78% in PMfine and 73% in PMcoarse), consistent with previous studies [7,14]. Hong et al [7] concluded that tire wear and diesel exhaust were the two greatest contributors to bioaccessible Zn in road dust. The bioaccessibility was the second highest for Mn (Figure 3b), which may reflect weathered soil minerals and/or Mnbased gasoline additives.…”

Section: Metal Bioaccessibility In Fine Versus Coarse Dust Fractionssupporting

confidence: 88%

“…A relatively new area of interest in the field of public health is the impact of resuspended road dust on human health, particularly on the respiratory and cardiovascular systems [6]. Road dust is a complex medium that is generated by the accumulation of particles derived mainly from vehicular exhaust and non-exhaust sources (particles emitted from tire and brake wear, road surface erosion and urban soil) [7]. Due to the turbulence created by road transportation and wind, resuspended road dust is recognized to be an important source of atmospheric PM, particularly in large urban centres [8,9].…”

Section: Introductionmentioning

confidence: 99%

“…As regulatory and legislative actions have helped to greatly reduce the levels of air pollutants in automotive exhaust in recent decades, the relative contribution of non-exhaust sources to atmospheric PM has increased [10]. Various studies have associated certain metals in atmospheric PM with the wear and tear of auto parts (e.g., Pb, Cu and Zn), gasoline and diesel emissions (Cr and Ni) [7], and exhaust catalysts (platinum, palladium and rhodium) [11]. Particular concerns have been raised about inhalation exposures to vehicular sources of transition metals (e.g., Zn, Mn and Cu), which generate reactive oxygen species (ROS) [12,13] and which tend to display high bioaccessibility in the respiratory tract [5].…”

Section: Introductionmentioning

confidence: 99%

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Thoracic Fraction (PM10) of Resuspended Urban Dust: Geochemistry, Particle Size Distribution and Lung Bioaccessibility

et al. 2021

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A fluidized bed aerosol generator was connected to a 13-stage cascade impactor (nanoMOUDI) for the size fractionation of urban dust (<10 µm), followed by the gravimetric analysis of loaded PTFE filter samples. This method was used to characterize the PM10 (thoracic) fraction of road dust sampled from expressways, arterial roads and local roads in Toronto, Canada. The fine particle fractions (<1.8 µm) of all the studied samples accounted for 51–72% of the resuspended PM10 (by weight). Elemental analysis using ICP-MS and ICP-OES revealed an overall trend of element enrichment in the <1.8 µm fraction compared to the coarse fraction (1.8–10 µm) of the road dust. By contrast, archived house dust samples displayed the reverse trend for most elements. The lung bioaccessibility of target elements (Al, B, Ba, Co, Cr, Fe, La, Mn, Mo, Sb, Sr, Ti, V and Zn) was assessed for each road dust fraction using 0.1 M ammonium citrate (pH 4.4) to simulate intracellular fluid and Gamble solution (pH 7.2) to simulate interstitial lung fluid. The <1.8 µm fraction of local road dust displayed significantly higher bioaccessibility (p < 0.05) for Zn when using Gamble solution, and for seven out of the 14 target elements when using ammonium citrate. These results show the importance of characterizing the fine fraction of road dust.

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Section: Metal Bioaccessibility In Fine Versus Coarse Dust Fractionssupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Thoracic Fraction (PM10) of Resuspended Urban Dust: Geochemistry, Particle Size Distribution and Lung Bioaccessibility

et al. 2021

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“…It is usually combined with the other elements in hundreds of minerals. In other words, the occurrence of Fe is strongly linked to the other metals 32 . Therefore, for a better modelling effect, Fe was selected as an input parameter.…”

Section: Study Area and Water Quality Datamentioning

confidence: 99%

A comparative analysis of artificial neural networks and wavelet hybrid approaches to long-term toxic heavy metal prediction

Hua

GUI

et al. 2020

Sci Rep

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the occurrence of toxic metals in the aquatic environment is as caused by a variety of contaminations which makes difficulty in the concentration prediction. In this study, conventional methods of backpropagation neural network (Bpnn) and nonlinear autoregressive network with exogenous inputs (NARX) were applied as benchmark models. Explanatory variables of Fe, pH, electrical conductivity, water temperature, river flow, nitrate nitrogen, and dissolved oxygen were used as different input combinations to forecast the long-term concentrations of As, Pb, and Zn. The wavelet transformation was applied to decompose the time series data, and then was integrated with conventional methods (as WNN and WNARX). The modelling performances of the hybrid models of WNN and WNARX were compared with the conventional models. All the given models were trained, validated, and tested by an 18-year data set and demonstrated based on the simulation results of a 2-year data set. Results revealed that the given models showed general good performances for the long-term prediction of the toxic metals of As, Pb, and Zn. The wavelet transform could enhance the long-term concentration predictions. However, it is not necessarily useful for each metal prediction. Therefore, different models with different inputs should be used for different metals predictions to achieve the best predictions. Due to the nature of ubiquity, toxicity at a trace level, and hard biodegradation, elevated metals in aquatic environments are a global concern 1,2. A long-term exposure of toxic metals by the ingestion of the contaminated water and fish can cause chronic diseases 3,4. For example, Arsenic (As) destroys the redox capacity of cells, affects the normal metabolism, causes tissue damage and body disorders, and even directly causes poisoning death when ingested in small quantities 5. Lead (Pb) affects nerves, digestion, urinary, reproductive and developmental, cardiovascular, endocrine, immune, bone, and other organ systems. More serious is that Pb affects the growth and mental development of infants and young children, impairs brain function such as cognition 6. In addition, a high level of Zinc (Zn) weakens immune function, leads to iron deficiency anaemia, affects the function of the digestive system, and causes damage to blood vessels 7. Due to the special significance to water quality, As, Pb, and Zn are included in the priority pollutant list by the United States Environmental Protection Agency. Therefore, it is essential to understand the environmental behaviours of toxic metal in rivers to protect the drinking water intake. Traditionally, the toxic metals in trace levels were required to be routinely sampled and determined in the laboratory. However, there are some constraints for the environmental managers to adequately and timely receive the metal contents and respond to the metal pollution, such as (i) expense of field monitoring, (ii) staffs availability and resources, (iii) field safety issues, and (iv) large time intervals between data collection, r...

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“…Roads, as an important linear landscape element, affect both abiotic and biotic ecosystems, especially the vegetation composition and soil properties along them [1,2]. In recent decades, studies on the ecological and environmental effects of road traffic have increased significantly [3][4][5][6]. In China, the development of road networks has been rapid with many high-level roads being constructed in recent years [7].…”

Section: Introductionmentioning

confidence: 99%

Effects of Landscape Features on the Roadside Soil Heavy Metal Distribution in a Tropical Area in Southwest China

et al. 2021

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Soil heavy metals along roadsides pose a great threat to ecosystems while their spatial variations and influencing factors still remain unclear in some regions, especially in tropical areas with complex landscape characteristics. Our study was carried out to determine how the land use, vegetation characteristics, topographical factors and distance to the road affect the soil heavy metal distribution. Taking Jinghong county in Yunnan Province, Southwest China as a case, soil samples were collected at different distances off roads and canonical correspondence analysis (CCA) methods were used to determine the relative importance of different factors. Our results showed that heavy metal sources were obtained mainly from the road, based on the principle component analysis (PCA) identification. There were no obvious trends of soil quality index (SQI) with distance to the road in natural soils, while SQI nutrients and SQI metals in farmlands had a decreasing and increasing trend, respectively, which could both be expressed by logarithm models. However, soil properties showed little differences for road levels while they showed significant differences under land use types. The CCA further showed that heavy metal variations in natural soils were jointly affected by distance, plant coverage, relative elevation and soil properties in decreasing order.

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Quantitative source tracking of heavy metals contained in urban road deposited sediments

Cited by 72 publications

References 52 publications

Thoracic Fraction (PM10) of Resuspended Urban Dust: Geochemistry, Particle Size Distribution and Lung Bioaccessibility

Thoracic Fraction (PM10) of Resuspended Urban Dust: Geochemistry, Particle Size Distribution and Lung Bioaccessibility

A comparative analysis of artificial neural networks and wavelet hybrid approaches to long-term toxic heavy metal prediction

Effects of Landscape Features on the Roadside Soil Heavy Metal Distribution in a Tropical Area in Southwest China

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