Investigation of contaminant profile in highway stormwater runoff and risk assessment by statistical analysis

Author:

Iqbal H.,Saleem M.,Bahadar A.,Hossain N.ORCID,Hanif M. U.,Waqas A.

Abstract

AbstractHighway stormwater runoff pollution has become a severe risk factor for water bodies nowadays. The conventional risk analysis protocols for directly discharging highway runoff are prone to systematic and judgmental errors. Therefore, a numeric and straightforward risk assessment protocol has been developed in this study that minimizes the errors. For this study, three highway segments were selected in the city of Rawalpindi, Pakistan. Event mean concentrations have been used as baseline numeric values for calculating the risk of discharging highway stormwater directly into the water bodies. These values are also correlated with highway characteristics (area, slope, and traffic count) and storm characteristics (storm depth, cumulative runoff volume, antecedent dry days, and cumulative flow). The highway stormwater was monitored for organics, metals, solids, and macro-nutrients at three highway sections. The event mean concentrations of dissolved organic carbon (50–145 mg/L), total suspended solids (1500–3900 mg/L), chromium (0.25–0.45 mg/L), and lead (0.1–0.8 mg/L) are found to be higher than the environmental quality standards. The risk assessment was conducted by the analysis of variance. The analysis showed that the highway characteristics significantly affect contaminant concentrations, but storm characteristics on contaminant concentrations are not found to be significant. Total suspended solids are the most threatening contaminant in highway runoffs. The study concluded that the risk from contaminants in highway stormwater depends particularly on the specific highway sections’ properties. The first flush portion (initial 25% of runoff) of highway runoff poses a higher threat to the receiving environment than the later runoff volumes.

Funder

Royal Melbourne Institute of Technology

Publisher

Springer Science and Business Media LLC

Subject

General Agricultural and Biological Sciences,Environmental Chemistry,Environmental Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Application of Artificial Intelligence and Fuzzy Control Algorithm in Green and Low-Carbon Highway Construction;International Journal of Computational Intelligence Systems;2024-09-04

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