For Libraries For Publication Open Access Downloads About Us Contact Us
Paper Titles
Clustering Daily Metro Origin-Destination Matrix in Shenzhen China
p.422
A Feasible Speed Profile Model for Automatic Train Protection System
p.433
Parking Choice Behavior for Shared Parking Based on Parking Purposes
p.439
Method for Evaluation of Railway Dynamic Safety Based on 5M Model and Neural Network Algorithm
p.445
Development of Prediction Models for Particle Size Composition on Urban Road Surfaces
p.450
2-D DOA Estimation of Quasi-Stationary Signals via Tensor Modeling
p.458
Passing Ability Evaluation and Impact Factors Analysis of Articulated Vehicle with 6×4 Tractor
p.463
Passing Ability Impact Factors Simulation of Articulated Vehicle with 6×4 Tractor
p.467
The Research of DOA Estimation Algorithms in the Conformal Array Antenna
p.471

Development of Prediction Models for Particle Size Composition on Urban Road Surfaces

Article Preview

Abstract:

It is commonly known that particles play a critical role in urban stormwater quality because other pollutants can be attached to the particles and transported into receiving waters. Previous research studies have shown a strong relationship between pollutant build-up loads and particle sizes. In this context, accurately estimating the particle amounts in different sizes is extremely important since it can assist in predicting stormwater quality and hence contribute to effective stormwater quality improvement measures. This paper presents a robust model to predict particle size composition on urban road surfaces using heavy-duty vehicle volumes, traffic coefficient and road texture depth by multiple linear regression (MLR) method. The pollutants build-up data was used for model development and was collected on typical urban roads in Shenzhen, China. The relative prediction error and coefficient of variation values were found within the acceptable limits and hence indicated that the developed prediction models are relatively reliable. This developed model can assist in predicting particle size composition on urban road surfaces and thereby contribute to effective stormwater quality assessment and treatment design. Additionally, this developed modelling approach can also provide a guide in terms of particle size composition prediction using more influential factors.

You might also be interested in these eBooks
Mechanical, Electronic and Information Technology Engineering View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 743)

Pages:

450-457

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.743.450

Citation:

Cite this paper

Online since:

March 2015

Authors:

An Liu, Liang Liu, Dun Zhu Li, Yun Tao Guan*

Keywords:

Particle Size Composition, Prediction Model, Solids Build-Up, Stormwater Runoff Quality, Traffic Characteristics

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

References

[1] N. Warren, I. J. Allan, J. E. Carter, W. A. House, A. Parker, Pesticides and other micro-organic contaminants in freshwater sedimentary environments – A review, Appl. Geochem. 18(2003) 159-194.

DOI: 10.1016/s0883-2927(02)00159-2

Google Scholar

[2] L. Herngren, A. Goonetilleke, G. A. Ayoko, Analysis of heavy metals in road-deposited sediments, Anal. Chim. Acta. 571(2006) 270-278.

DOI: 10.1016/j.aca.2006.04.064

Google Scholar

[3] N.P. Miguntanna, A. Liu, P. Egodawatta, A. Goonetilleke, Characterising nutrients wash-off for effective urban stormwater treatment design, J. Environ. Manage. 120 (2013) 61-67.

DOI: 10.1016/j.jenvman.2013.02.027

Google Scholar

[4] J. Vaze, F. H. S. Chiew, Experimental study of pollutant accumulation on an urban road surface, Urban Water. 4(2002) 379-389.

DOI: 10.1016/s1462-0758(02)00027-4

Google Scholar

[5] C. Gunawardana, P. Egodawatta, A. Goonetilleke, Role of particle size and composition in metal adsorption by solids deposited on urban road surfaces, Environ. Pollut. 184 (2014) 44-53.

DOI: 10.1016/j.envpol.2013.08.010

Google Scholar

[6] E. C. Prestes, V. E. Dos Anjos, F. F. Sodre, M. T. Grassi, Copper, lead and cadmium loads and behavior in urban stormwater runoff in Curitiba, Brazil, J. Brazil. Chem. Soc. 17 (2006) 53-60.

DOI: 10.1590/s0103-50532006000100008

Google Scholar

[7] I. Ujevic, N. Odzak, A. Baric, Trace metal accumulation in different grain size fractions of the sediments from a semi-enclosed bay heavily contaminated by urban and industrial wastewaters, Water Res. 34 (2000) 3055-3061.

DOI: 10.1016/s0043-1354(99)00376-0

Google Scholar

[8] H. T. Zhao, X. Y. Li, X. M. Wang, D. Tian, Grain size distribution of road-deposited sediment and its contribution to heavy metal pollution in urban runoff in Beijing, China, J. Hazard. Mater. 183 (2010) 203-210.

DOI: 10.1016/j.jhazmat.2010.07.012

Google Scholar

[9] X. J. Zuo, D. F. Fu, H. Li., R.P. Singh, Distribution characteristics of pollutants and their mutual influence in highway runoff, CLEAN-Soil. Air. Water. 39 (2011) 956-963.

DOI: 10.1002/clen.201000422

Google Scholar

[10] P. Mahbub, G. A. Ayoko, A. Goonetilleke, P. Egodawatta, S. Kokot, Impacts of traffic and rainfall characteristics on heavy metals build-up and wash-off from urban roads, Environ. Sci. Technol. 44 (2010) 8904-8910.

DOI: 10.1021/es1012565

Google Scholar

[11] P. Mahbub, A. Goonetilleke, G.A. Ayoko, Prediction model of the buildup of volatile organic compounds on urban roads, Environ. Sci. Technol.  45 (2011) 4453-4459.

DOI: 10.1021/es200307x

Google Scholar

[12] Transport Commission of Shenzhen Municipality (TCSM), Information on http: /szmap. sutpc. com/roadcongmore. aspx?page=1.

Google Scholar

[13] R. Pitt, R. Field, M. Lalor, M. Brown, Urban stormwater toxic pollutants: assessment, sources, and treatability, Water Environ. Res. 67 (1995) 260-275.

DOI: 10.2175/106143095x131466

Google Scholar

[14] M. L. Kreider, J. M. Panko, B. L. McAtee, L. I. Sweet, B. L. Finley, Physical and chemical characterization of tire-related particles: Comparison of particles generated using different methodologies, Sci. Total Environ. 408 (2010) 652-659.

DOI: 10.1016/j.scitotenv.2009.10.016

Google Scholar

[15] P. Egodawatta, A. Goonetilleke, Characteristics of pollution build-up on residential road surfaces. In M. Piasecki, S. Wang, K. Holz, M. Kawahara, A. Gonzalez, B. Beran (Eds. ), 7th International Conference on Hydroscience and Engineering, 10-13 September, 2006, Drexel University, Philadelphia.

Google Scholar

[16] APHA, Standard methods for the examination of Water and Waste Water, American Public Health Association, Washington DC, (2005).

Google Scholar

[17] StatistiXL, StatistiXL manual, Australia, (2007).

Google Scholar

[18] H. Abdi, Factor rotations, In: M. Lewis-Beck, A. Bryman, T. Futing (Eds), Encyclopedia for Research Methods for the Social Sciences, SAGE, Thousand Oaks (CA), (2003) 978-982.

Google Scholar

[19] D.J. Scott, K. Russell, J. Scheffer, Multi-Variable relationships in a batch annealing process. Statistics Department, The University of Auckland. Auckland, New Zealand, (2007).

Google Scholar

[20] P. Egodawatta, A. M. Ziyath, A. Goonetilleke, Characterising metal build-up on urban road surfaces,  Environ. Pollut. 176 (2013) 87-91.

DOI: 10.1016/j.envpol.2013.01.021

Google Scholar

[21] Y. Ni, L. Wang, S. Kokot, Simultaneous determination of nitrobenzene and nitro-substituted phenols by differential pulse voltammetry and chemometrics, Anal. Chim. Acta. 431(2001) 101-113.

DOI: 10.1016/s0003-2670(00)01319-2

Google Scholar

[22] W. Horwitz, Evaluation of Analytical Methods Used for Regulation of Foods and Drugs, Anal. Chem. 54 (1982) 67A-76A.

DOI: 10.1021/ac00238a765

Google Scholar

© 2025 Trans Tech Publications Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For open access content, terms of the Creative Commons licensing CC-BY are applied.
Scientific.Net is a registered trademark of Trans Tech Publications Ltd.