Index models to evaluate the potential metal pollution contribution from washoff of road-deposited sediment

Zhao, Hongtao; Zhao, Jiang; Yin, Chengqing; Li, Xuyong

doi:10.1016/j.watres.2014.04.012

Cited by 45 publications

(18 citation statements)

References 23 publications

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“…The effect of rainfall intensity on the washing surface and umbrella skirt edge of insulators is completely satisfied by washing modeling verified by experiment [27,28]. The residual wash-off ESDD and NSDD on the surfaces of insulators decreases with the intensity and duration of the rainfall, which meets the power function, exponential function, or other functions.…”

Section: Pollution Wash-off Modelmentioning

confidence: 55%

Investigating the Effect of Rainfall Parameters on the Self-Cleaning of Polluted Suspension Insulators: Insight from Southern China

Jiang

Zhang

et al. 2017

Energies

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The cleaning effect of heavy rain (the rainfall reaches 5 mm every day) on surface contamination of insulators is more effective than dew, fog, mist, and other light rain conditions which can initiate leakage currents and increase the likelihood of flashover. It is well understood that heavy rain can wash away contamination from the surface of high voltage (HV) insulators and thereby reduce the risk of pollution flashover. This study examines the cleaning effect of natural wetting conditions on HV insulators on four 500 kV transmission lines in Hunan Province, China. Historical meteorological data, monthly equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD) measurements taken over a period of five years were analyzed to investigate the relationship between rainfall intensity and insulator cleaning. The measured data show that the ESDD/NSDD changes with the seasonal variation, which accumulates in dry season (January-April, about 117-122 days) and is washed off in the wet season (June-October, about 118-127 days). According to the measured data, the ESDD and NSDD on the surface of insulators were affected by the rainfall intensity (in the dry season it is about 1 mm/day and in the wet season it is about 5 mm/day). Based on a comparison of the four study sites, we propose a mathematical model to show the functional relationship between rainfall intensity and insulator self-cleaning capability. The mathematical model's coefficient of determination (R 2 ) is greater than 0.9 and the effective rate of self-cleaning capability reaches 80%.illogical combinations, such as agricultural and desert conditions, do occur in winter in some areas [4][5][6]. Due to the high accumulation rates of natural contamination from industry and agriculture on insulator surfaces in Southern China during the winter months, an insulator cleaning program has been devised for transmission lines in the region [7,8]. However, the cleaning scheme is always carried out in December and only once for every year, therefore it is not very effective and the insulator surface could not maintain cleanliness for the whole year. The accumulation of contamination will increase with the air pollution after a few months. Thereby, it endangers the safe operation of power networks.The accumulation of contamination is mainly divided into two processes: contamination of HV insulators is highest during the dry season and lowest during the wet season, when rainfall efficiently removes some of the surface contaminants [9,10]. At present, the research mainly focuses on the pollution accumulation process, studies on air quality index (AQI), size and gravity of particles, wind speed, electric field intensity, and the force of adhesion, etc. [11,12]. However, there have been few studies on the effect of rainfall flushing. The existing research relies on artificial rainfall experiment platforms [13][14][15][16]. However, artificial pollution tests on outdoor insulators mostly consider the parameters of ideal conditions and the test results are n...

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Section: Pollution Wash-off Modelmentioning

confidence: 55%

Investigating the Effect of Rainfall Parameters on the Self-Cleaning of Polluted Suspension Insulators: Insight from Southern China

Jiang

Zhang

et al. 2017

Energies

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“…The confidence interval of a Cv will be used to illustrate the expected accuracy with which the Cv parameter was estimated. We used RDS in areas near main roads (R1) and residential areas (R2) in Beijing that were determined in our previous studies [ 9 , 24 ]. All of the study sites were within the metropolitan Beijing area.…”

Section: Resultsmentioning

confidence: 99%

Quantifying Grain-Size Variability of Metal Pollutants in Road-Deposited Sediments Using the Coefficient of Variation

Zhao

Wang

2017

IJERPH

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Particle grain size is an important indicator for the variability in physical characteristics and pollutants composition of road-deposited sediments (RDS). Quantitative assessment of the grain-size variability in RDS amount, metal concentration, metal load and GSFLoad is essential to elimination of the uncertainty it causes in estimation of RDS emission load and formulation of control strategies. In this study, grain-size variability was explored and quantified using the coefficient of variation (Cv) of the particle size compositions, metal concentrations, metal loads, and GSFLoad values in RDS. Several trends in grain-size variability of RDS were identified: (i) the medium class (105–450 µm) variability in terms of particle size composition, metal loads, and GSFLoad values in RDS was smaller than the fine (<105 µm) and coarse (450–2000 µm) class; (ii) The grain-size variability in terms of metal concentrations increased as the particle size increased, while the metal concentrations decreased; (iii) When compared to the Lorenz coefficient (Lc), the Cv was similarly effective at describing the grain-size variability, whereas it is simpler to calculate because it did not require the data to be pre-processed. The results of this study will facilitate identification of the uncertainty in modelling RDS caused by grain-size class variability.

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“…Certified geochemical soil reference materials (CRMs) GSS-1 and GSS-2 were also analyzed to provide quality assurance and quality control (QA/QC) information. The analytical methods and quality control procedures have been described in detail (Zhao et al, 2014a).…”

Section: Analytical Methods and Quality Controlmentioning

confidence: 99%

An index for estimating the potential metal pollution contribution to atmospheric particulate matter from road dust in Beijing

Zhao

Shao

Yin

et al. 2016

Science of The Total Environment

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• An innovative road dust index was developed.• Road dust characteristics were ranked and weighted in the index model.• Source and transport factors were both considered in the index model. The resuspension of road dust from street surfaces could be a big contributor to atmospheric particulate pollution in the rapid urbanization context in the world. However, to date what its potential contribution to the spatial pattern is little known. Here we developed an innovative index model called the road dust index (RI b105 μm ) and it combines source and transport factors for road dust particles b 105 μm in diameter. It could quantify and differentiate the impact of the spatial distribution of the potential risks posed by metals associated with road dust on atmospheric suspended particles. The factors were ranked and weighted based on road dust characteristics (the amounts, grain sizes, and mobilities of the road dust, and the concentrations and toxicities of metals in the road dust). We then applied the RI b105 μm in the Beijing region to assess the spatial distribution of the potential risks posed by metals associated with road dust on atmospheric suspended particles. The results demonstrated that the road dust in urban areas has higher potential risk of metal to atmospheric particles than that in rural areas. The RI b105 μm method offers a new and useful tool for assessing the potential risks posed by metals associated with road dust on atmospheric suspended particles and for controlling atmospheric particulate pollution caused by road dust emissions.

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Index models to evaluate the potential metal pollution contribution from washoff of road-deposited sediment

Cited by 45 publications

References 23 publications

Investigating the Effect of Rainfall Parameters on the Self-Cleaning of Polluted Suspension Insulators: Insight from Southern China

Investigating the Effect of Rainfall Parameters on the Self-Cleaning of Polluted Suspension Insulators: Insight from Southern China

Quantifying Grain-Size Variability of Metal Pollutants in Road-Deposited Sediments Using the Coefficient of Variation

An index for estimating the potential metal pollution contribution to atmospheric particulate matter from road dust in Beijing

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