Development of prediction models for particle size composition on urban road surfaces

摘要

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.