American Society of Civil Engineers


Asphalt Parking Lot Runoff Nutrient Characterization for Eight Sites in North Carolina, USA


by Elodie Passeport, (Grad. Res. Asst., Dept. of Biological and Agric. Engrg., North Carolina State Univ., Raleigh, NC 27695-7625) and William F. Hunt, (Asst. Prof. and Extension Specialist, Dept. of Biological and Agric. Engrg., North Carolina State Univ., Raleigh, NC 27695-7625. E-mail: bill_hunt@ncsu.edu)

Journal of Hydrologic Engineering, Vol. 14, No. 4, April 2009, pp. 352-361, (doi:  http://dx.doi.org/10.1061/(ASCE)1084-0699(2009)14:4(352))

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Document type: Journal Paper
Special Issue: Impervious Surfaces in Hydrologic Modeling and Monitoring
Abstract: The objectives of this study were to characterize asphalt parking lot runoff quality and determine factors influencing nutrient concentrations and loads. Event mean concentrations (EMCs) and loads were measured from eight asphalt parking lots in North Carolina using automated flow meters and rain gauges. The number of water quality samples collected varied from 11 to 26 per site. EMCs and loads were statistically analyzed for six nutrient forms: total nitrogen, total Kjeldahl nitrogen, ammonia-nitrogen, nitrate-nitrogen, total phosphorus, and ortho-phosphate. The mean EMCs (in mg/L) were 1.57, 1.19, 0.32, 0.36, 0.19 and 0.07, respectively. Nitrogen species’ concentrations were slightly lower than those from highway runoff found in the literature; whereas, phosphorus EMCs were similar to those in highway runoff. Current load prediction models, generally based on highway or roadway nutrient concentrations, are therefore expected to over-estimate nitrogen loads from asphalt parking lots. Spring and summer presented the highest EMCs and loads, respectively. Significant seasonal differences in concentration (p<0.05) were found mainly between spring and the other three seasons, while loads in summer differed from those of fall and winter. In an attempt to determine the factors affecting EMCs and loads, Pearson correlation tests and multiple linear regression analyses were performed. Strong correlations were found among the variables of each group of factors referred to as climate, physical characteristics and surrounding land use. Rainfall depth, catchment area, the percentage of asphalt and natural surrounding land use were good predictors of nutrient concentrations and loads.


ASCE Subject Headings:
Asphalt pavements
Nutrients
Runoff
Regression analysis
Parking facilities
Water quality
Stormwater management